Tag Archive: Learning

KEY FEATURES

Businesses today have access to more data than ever before, and a key challenge is ensuring that data can be easily accessed and used efficiently. MongoDB makes it possible to store and process large sets of data in a ways that drive up business value. Learning MongoDB will give you the flexibility of unstructured storage, combined with robust querying and post processing functionality, making you an asset to enterprise Big Data needs.

• Access 64 lectures & 40 hours of content 24/7
• Master data management, queries, post processing, & essential enterprise redundancy requirements
• Explore advanced data analysis using both MapReduce & the MongoDB aggregation framework
• Delve into SSL security & programmatic access using various languages
• Learn about MongoDB’s built-in redundancy & scale features, replica sets, & sharding

PRODUCT SPECS

Details & Requirements

• Length of time users can access this course: lifetime
• Access options: web streaming, mobile streaming
• Certification of completion included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: all levels

Compatibility

• Internet required

THE EXPERT

Daniel Watrous is a 15-year veteran of designing web-enabled software. His focus on data store technologies spans relational databases, caching systems, and contemporary NoSQL stores. For the last six years, he has designed and deployed enterprise-scale MongoDB solutions in semiconductor manufacturing and information technology companies. He holds a degree in electrical engineering from the University of Utah, focusing on semiconductor physics and optoelectronics. He also completed an MBA from the Northwest Nazarene University. In his current position as senior cloud architect with Hewlett Packard, he focuses on highly scalable cloud-native software systems.

KEY FEATURES

A/B testing is used everywhere, from marketing, retail, news feeds, online advertising, and much more. If you’re a data scientist, and you want to tell the rest of the company, “logo A is better than logo B,” you’re going to need numbers and stats to prove it. That’s where A/B testing comes in. In this course, you’ll do traditional A/B testing in order to appreciate its complexity as you elevate towards the Bayesian machine learning way of doing things.

• Access 40 lectures & 3.5 hours of content 24/7
• Improve on traditional A/B testing w/ adaptive methods
• Learn about epsilon-greedy algorithm & improve upon it w/ a similar algorithm called UCB1
• Understand how to use a fully Bayesian approach to A/B testing

PRODUCT SPECS

Details & Requirements

• Length of time users can access this course: lifetime
• Access options: web streaming, mobile streaming
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: all levels, but knowledge of calculus, probability, Python, Numpy, Scipy, and Matplotlib is expected
• All code for this course is available for download here, in the directory ab_testing

Compatibility

• Internet required

THE EXPERT

The Lazy Programmer is a data scientist, big data engineer, and full stack software engineer. For his master’s thesis he worked on brain-computer interfaces using machine learning. These assist non-verbal and non-mobile persons to communicate with their family and caregivers.

He has worked in online advertising and digital media as both a data scientist and big data engineer, and built various high-throughput web services around said data. He has created new big data pipelines using Hadoop/Pig/MapReduce, and created machine learning models to predict click-through rate, news feed recommender systems using linear regression, Bayesian Bandits, and collaborative filtering and validated the results using A/B testing.

He has taught undergraduate and graduate students in data science, statistics, machine learning, algorithms, calculus, computer graphics, and physics for students attending universities such as Columbia University, NYU, Humber College, and The New School.

Multiple businesses have benefitted from his web programming expertise. He does all the backend (server), frontend (HTML/JS/CSS), and operations/deployment work. Some of the technologies he has used are: Python, Ruby/Rails, PHP, Bootstrap, jQuery (Javascript), Backbone, and Angular. For storage/databases he has used MySQL, Postgres, Redis, MongoDB, and more.

KEY FEATURES

Variational autoencoders and GANs have been two of the most interesting recent developments in deep learning and machine learning. GAN stands for generative adversarial network, where two neural networks compete with each other. Unsupervised learning means you’re not trying to map input data to targets, you’re just trying to learn the structure of that input data. In this course, you’ll learn the structure of data in order to produce more stuff that resembles the original data.

• Access 41 lectures & 5.5 hours of content 24/7
• Incorporate ideas from Bayesian Machine Learning, Reinforcement Learning, & Game Theory
• Discuss variational autoencoder architecture
• Discover GAN basics

PRODUCT SPECS

Details & Requirements

• Length of time users can access this course: lifetime
• Access options: web streaming, mobile streaming
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: all levels, but knowledge of calculus, probability, object-oriented programming, Python, Numpy, linear regression, gradient descent, and how to build a feedforward and convolutional neural network in Theano and TensorFlow is expected
• All code for this course is available for download here, in the directory unsupervised_class3

Compatibility

• Internet required

THE EXPERT

The Lazy Programmer is a data scientist, big data engineer, and full stack software engineer. For his master’s thesis he worked on brain-computer interfaces using machine learning. These assist non-verbal and non-mobile persons to communicate with their family and caregivers.

He has worked in online advertising and digital media as both a data scientist and big data engineer, and built various high-throughput web services around said data. He has created new big data pipelines using Hadoop/Pig/MapReduce, and created machine learning models to predict click-through rate, news feed recommender systems using linear regression, Bayesian Bandits, and collaborative filtering and validated the results using A/B testing.

He has taught undergraduate and graduate students in data science, statistics, machine learning, algorithms, calculus, computer graphics, and physics for students attending universities such as Columbia University, NYU, Humber College, and The New School.

Multiple businesses have benefitted from his web programming expertise. He does all the backend (server), frontend (HTML/JS/CSS), and operations/deployment work. Some of the technologies he has used are: Python, Ruby/Rails, PHP, Bootstrap, jQuery (Javascript), Backbone, and Angular. For storage/databases he has used MySQL, Postgres, Redis, MongoDB, and more.

KEY FEATURES

This course is all about the application of deep learning and neural networks to reinforcement learning. The combination of deep learning with reinforcement learning has led to AlphaGo beating a world champion in the strategy game Go, it has led to self-driving cars, and it has led to machines that can play video games at a superhuman level. Unlike supervised and unsupervised learning algorithms, reinforcement learning agents have an impetus—they want to reach a goal. In this course, you’ll work with more complex environments, specifically, those provided by the OpenAI Gym.

• Access 52 lectures & 5 hours of content 24/7
• Extend your knowledge of temporal difference learning by looking at the TD Lambda algorithm
• Explore a special type of neural network called the RBF network
• Look at the policy gradient method
• Examine Deep Q-Learning

PRODUCT SPECS

Details & Requirements

• Length of time users can access this course: lifetime
• Access options: web streaming, mobile streaming
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: all levels, but knowledge of calculus, probability, object-oriented programming, Python, Numpy, linear regression, gradient descent, how to build a feedforward and convolutional neural network in Theano and TensorFlow, Markov Decision Processes, and how to implement Dynamic Programming, Monte Carlo, and Temporal Difference is expected
• All code for this course is available for download here, in the directory rl2

Compatibility

• Internet required

THE EXPERT

The Lazy Programmer is a data scientist, big data engineer, and full stack software engineer. For his master’s thesis he worked on brain-computer interfaces using machine learning. These assist non-verbal and non-mobile persons to communicate with their family and caregivers.

He has worked in online advertising and digital media as both a data scientist and big data engineer, and built various high-throughput web services around said data. He has created new big data pipelines using Hadoop/Pig/MapReduce, and created machine learning models to predict click-through rate, news feed recommender systems using linear regression, Bayesian Bandits, and collaborative filtering and validated the results using A/B testing.

He has taught undergraduate and graduate students in data science, statistics, machine learning, algorithms, calculus, computer graphics, and physics for students attending universities such as Columbia University, NYU, Humber College, and The New School.

Multiple businesses have benefitted from his web programming expertise. He does all the backend (server), frontend (HTML/JS/CSS), and operations/deployment work. Some of the technologies he has used are: Python, Ruby/Rails, PHP, Bootstrap, jQuery (Javascript), Backbone, and Angular. For storage/databases he has used MySQL, Postgres, Redis, MongoDB, and more.

KEY FEATURES

When people talk about artificial intelligence, they usually don’t mean supervised and unsupervised machine learning. These tasks are pretty trivial compared to what we think of AIs doing—playing chess and Go, driving cars, etc. Reinforcement learning has recently become popular for doing all of that and more. Reinforcement learning opens up a whole new world. It’s lead to new and amazing insights both in behavioral psychology and neuroscience. It’s the closest thing we have so far to a true general artificial intelligence, and this course will be your introduction.

• Access 71 lectures & 5.5 hours of content 24/7
• Discuss the multi-armed bandit problem & the explore-exploit dilemma
• Learn ways to calculate means & moving averages and their relationship to stochastic gradient descent
• Explore Markov Decision Processes, Dynamic Programming, Monte Carlo, & Temporal Difference Learning
• Understand approximation methods

PRODUCT SPECS

Details & Requirements

• Length of time users can access this course: lifetime
• Access options: web streaming, mobile streaming
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: all levels, but knowledge of calculus, probability, object-oriented programming, Python, Numpy, linear regression, and gradient descent is expected
• All code for this course is available for download here, in the directory rl

Compatibility

• Internet required

THE EXPERT

The Lazy Programmer is a data scientist, big data engineer, and full stack software engineer. For his master’s thesis he worked on brain-computer interfaces using machine learning. These assist non-verbal and non-mobile persons to communicate with their family and caregivers.

He has worked in online advertising and digital media as both a data scientist and big data engineer, and built various high-throughput web services around said data. He has created new big data pipelines using Hadoop/Pig/MapReduce, and created machine learning models to predict click-through rate, news feed recommender systems using linear regression, Bayesian Bandits, and collaborative filtering and validated the results using A/B testing.

He has taught undergraduate and graduate students in data science, statistics, machine learning, algorithms, calculus, computer graphics, and physics for students attending universities such as Columbia University, NYU, Humber College, and The New School.

Multiple businesses have benefitted from his web programming expertise. He does all the backend (server), frontend (HTML/JS/CSS), and operations/deployment work. Some of the technologies he has used are: Python, Ruby/Rails, PHP, Bootstrap, jQuery (Javascript), Backbone, and Angular. For storage/databases he has used MySQL, Postgres, Redis, MongoDB, and more.

KEY FEATURES

You’ve seen deep learning everywhere, but you may not have realized it. This discipline is one of the leading solutions for image recognition, speech recognition, object recognition, and language translation – basically the tools you see Google roll out every day. Over this course, you’ll use Python to expand your deep learning knowledge to cover backpropagation and its ability to train neural networks.

• Access 19 lectures & 2 hours of content 24/7
• Train neural networks in deep learning & to understand automatic differentiation
• Cover convolutional & recurrent neural networks
• Build up the theory that covers supervised learning
• Integrate search & image recognition, & object processing
• Examine the performance of the sentimental analysis model

PRODUCT SPECS

Details & Requirements

• Length of time users can access this course: lifetime
• Access options: web streaming, mobile streaming
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: all levels

Compatibility

• Internet required

THE EXPERT

Eder Santana is a PhD candidate in Electrical and Computer Engineering. His thesis topic is on Deep and Recurrent neural networks. After working for 3 years with Kernel Machines (SVMs, Information Theoretic Learning, and so on), Eder moved to the field of deep learning 2.5 years ago, when he started learning Theano, Caffe, and other machine learning frameworks. Now, Eder contributes to Keras: Deep Learning Library for Python. Besides deep learning, he also likes data visualization and teaching machine learning, either on online forums or as a teacher assistant.

KEY FEATURES

Deep learning is the intersection of statistics, artificial intelligence, and data to build accurate models, and is one of the most important new frontiers in technology. TensorFlow is one of the newest and most comprehensive libraries for implementing deep learning. Over this course you’ll explore some of the possibilities of deep learning, and how to use TensorFlow to process data more effectively than ever.

• Access 22 lectures & 2 hours of content 24/7
• Discover the efficiency & simplicity of TensorFlow
• Process & change how you look at data
• Sift for hidden layers of abstraction using raw data
• Train your machine to craft new features to make sense of deeper layers of data
• Explore logistic regression, convolutional neural networks, recurrent neural networks, high level interfaces, & more

PRODUCT SPECS

Details & Requirements

• Length of time users can access this course: lifetime
• Access options: web streaming, mobile streaming
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: all levels

Compatibility

• Internet required

THE EXPERT

Dan Van Boxel is a Data Scientist and Machine Learning Engineer with over 10 years of experience. He is most well-known for “Dan Does Data,” a YouTube livestream demonstrating the power and pitfalls of neural networks. He has developed and applied novel statistical models of machine learning to topics such as accounting for truck traffic on highways, travel time outlier detection, and other areas. Dan has also published research and presented findings at the Transportation Research Board and other academic journals.

KEY FEATURES

AI and Deep Learning are transforming the way we understand software, making computers more intelligent than we could even imagine just a decade ago. Starting with an introduction to basic machine learning algorithms, this course takes you further into this vital world of stunning predictive insights and remarkable machine intelligence.

• Access 254 pages of content 24/7
• Get a practical deep dive into machine learning & deep learning algorithms
• Implement machine learning algorithms related to deep learning
• Explore neural networks using some of the most popular Deep Learning frameworks
• Dive into Deep Belief Nets & Stacked Denoising Autoencoders algorithms
• Discover more deep learning algorithms w/ Dropout & Convolutional Neural Networks
• Gain an insight into the deep learning library DL4J & its practical uses
• Get to know device strategies to use deep learning algorithms & libraries in the real world
• Explore deep learning further w/ Theano & Caffe

PRODUCT SPECS

Details & Requirements

• Length of time users can access this course: lifetime
• Access options: web streaming, mobile streaming
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: all levels

Compatibility

• Internet required

THE EXPERT

Packt’s mission is to help the world put software to work in new ways, through the delivery of effective learning and information services to IT professionals. Working towards that vision, it has published over 3,000 books and videos so far, providing IT professionals with the actionable knowledge they need to get the job done–whether that’s specific learning on an emerging technology or optimizing key skills in more established tools.

KEY FEATURES

Artificial Intelligence is especially relevant in today’s technology and data-driven world. It’s used in search engines, image recognition, robotics, finance, and many other industries. In this book, you’ll explore various real-world scenarios while learning about various algorithms that can be used to build AI applications. Starting out from the basics of AI, you’ll learn how to develop various building blocks using different data mining techniques before delving into more advanced subjects.

• Access 446 pages of digital content 24/7
• Explore different classification & regression techniques
• Understand the concept of clustering & how to use it to automatically segment data
• See how to build an intelligent recommender system
• Discover logic programming & how to use it
• Build automatic speech recognition systems
• Understand the basics of heuristic search & genetic programming
• Develop games using Artificial Intelligence
• Learn how reinforcement learning works
• Discover how to build intelligent applications centered on images, text, & time series data
• See how to use deep learning algorithms & build applications based on them

PRODUCT SPECS

Details & Requirements

• Length of time users can access this course: lifetime
• Access options: web streaming, mobile streaming
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: all levels

Compatibility

• Internet required

THE EXPERT

Packt’s mission is to help the world put software to work in new ways, through the delivery of effective learning and information services to IT professionals. Working towards that vision, it has published over 4,000 books and videos so far, providing IT professionals with the actionable knowledge they need to get the job done–whether that’s specific learning on an emerging technology or optimizing key skills in more established tools.

KEY FEATURES

This book will teach you how to deploy large-scale datasets in deep neural networks with Hadoop for optimal performance. Starting with an introduction to deep learning, you’ll learn how to set up a Hadoop envrionment and implement a variety of deep learning models. By the end of the book, you’ll know how to deploy various deep neural networks in distributed systems using Hadoop.

• Access 206 pages of digital content 24/7
• Explore deep learning & various models associated w/ it
• Understand the challenges of implementing distributed deep learning w/ Hadoop & how to overcome it
• Implement Convolutional Neural Network (CNN) w/ deeplearning4j
• Delve into the implementation of Restricted Boltzmann Machines (RBM)
• Understand the mathematical explanation for implement Recurrent Neural Networks (RNN)
• Get hands on practice w/ deep learning with Hadoop

PRODUCT SPECS

• Length of time users can access this course: lifetime
• Access options: web streaming, mobile streaming
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: all levels

Compatibility

• Internet required

THE EXPERT

Packt’s mission is to help the world put software to work in new ways, through the delivery of effective learning and information services to IT professionals. Working towards that vision, it has published over 4,000 books and videos so far, providing IT professionals with the actionable knowledge they need to get the job done–whether that’s specific learning on an emerging technology or optimizing key skills in more established tools.

KEY FEATURES

This book starts by introducing you to supervised learning algorithms such as simple linear regression, the classical multilayer peceptron, and more sophisticated deep convolutional networks. You’ll also explore image processing, Recurrent Networks, and unsupervised learning algorithms such as Autoencoders. Finally, you’ll take a look at Reinforcement Learning and its application to AI game playing, another popular direction of research and application of neural networks.

• Access 318 pages of digital content 24/7
• Optimize step-by-step functions on a large neural network using the Backpropagation Algorithm
• Fine tune a neural network to improve the quality of results
• Use deep learning for image & audio processing
• Utilize Recursive Neural Tensor Networks (RNTNs) to outperform standard word embedding in special cases
• Identify problems for which Recurrent Neural Network (RNN) solutions are suitable
• Explore the process required to implement Autoencoders
• Evolve a deep neural network using reinforcement learning

PRODUCT SPECS

Details & Requirements

• Length of time users can access this course: lifetime
• Access options: web streaming, mobile streaming
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: all levels

Compatibility

• Internet required

THE EXPERT

Packt’s mission is to help the world put software to work in new ways, through the delivery of effective learning and information services to IT professionals. Working towards that vision, it has published over 4,000 books and videos so far, providing IT professionals with the actionable knowledge they need to get the job done–whether that’s specific learning on an emerging technology or optimizing key skills in more established tools.

KEY FEATURES

In this course, you’ll examine in detail the R programming language, the most popular statistical programming language in the world today. You’ll start by exploring different learning methods, clustering, classification, model evaluation methods and performance metrics. As you progress to more advanced subjects, you’ll develop the skills necessary to perform a variety of tasks with R.

• Access 35 lectures & 4 hours of content 24/7
• Delve into the general structure of clustering algorithms
• Develop applications in the R environment by using clustering & classification algorithms for real-life problems
• Use general definitions about artificial neural networks
• Explore the elements of deep learning neural networks & other types of deep learning networks
• Dive into developing machine learning algorithms w/ SparkR

PRODUCT SPECS

Details & Requirements

• Length of time users can access this course: lifetime
• Access options: web streaming, mobile streaming
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: all levels

Compatibility

• Internet required

THE EXPERT

Olgun is PhD candidate at Department of Statistics, Mimar Sinan University. He has been working on Deep Learning for his PhD thesis. Also working as Data Scientist.He is so familiar with Big Data technologies like Hadoop, Spark and able to use Hive, Impala. He is a big fan of R. Also he really loves to work with Shiny, SparkR.He has many academic papers and proceedings about applications of statistics on different disciplines. Mr. Olgun really loves statistic and loves to investigate new methods, share his experience with people.

KEY FEATURES

Deep learning is the step that comes after machine learning, and has more advanced implementations. Throughout this book, you’ll learn how to implement deep learning algorithms for machine learning systems and integrate them into your product offerings, including search, image recognition, and language processing. After finishing the book, you’ll be familiar with machine learning techniques, in particular the use of TensorFlow for deep learning.

• Access 320 pages of digital content 24/7
• Learn about machine learning landscapes along w/ the historical development & progress of deep learning
• Discuss deep machine intelligence & GPU computing w/ the latest TensorFlow 1.x
• Access public datasets & utilize them using TensorFlow to load, process, and transform data
• Use TensorFlow on real-world datasets, including images, text, & more
• Learn how to evaluate the performance of your deep learning models
• Use deep learning for scalable object detection & mobile computing
• Train machines quickly to learn from data by exploring reinforcement learning techniques
• Explore active areas of deep learning research & applications

PRODUCT SPECS

Details & Requirements

• Length of time users can access this course: lifetime
• Access options: web streaming, mobile streaming
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: all levels

Compatibility

• Internet required

THE EXPERT

Packt’s mission is to help the world put software to work in new ways, through the delivery of effective learning and information services to IT professionals. Working towards that vision, it has published over 4,000 books and videos so far, providing IT professionals with the actionable knowledge they need to get the job done–whether that’s specific learning on an emerging technology or optimizing key skills in more established tools.

KEY FEATURES

AI and deep learning are transforming the way we understand software, making computers more intelligent than we could imagine even a decade ago. Deep learning algorithms are being used across a broad range of industries to produce hardware like self-driving cars, personal assistant computers, and decision support systems. As the fundamental driver of AI, Java is becoming a more vital and valuable skill in the global economy, and this course will introduce you to using Java for deep learning.

• Access 20 lectures & 2 hours of content 24/7
• Install the environment precisely
• Use the DL4J & apply deep learning to a range of real-world use cases
• Get an introduction to neural networks & implementing them
• Learn about various deep learning algorithms
• Tune Apache Spark

PRODUCT SPECS

Details & Requirements

• Length of time users can access this course: lifetime
• Access options: web streaming, mobile streaming
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: all levels

Compatibility

• Internet required

THE EXPERT

Sercan Karaoglu gained his BSc in Mathematics Engineering at Istanbul Technical University. Karaoglu also completed a Research and Development project at age 23, at Foreks, in collaboration with The Scientific and Technological Research Council of Turkey(TUBITAK). This project was related to the application of Artificial Neural Networks in Financial Trading Decision Support Systems and Market Simulation for Intraday and Daily Trading.

Currently, he develops High Throughput-Low Latency Reactive Microservices and Reactive Stream applications at work and researches the topics of Deep Learning and Machine Learning. He is Java Software Engineer at the Dissemination Department of Foreks Information Systems, which is one of the leading IT companies in Turkey’s financial sector. It has specialized in software that is directly integrated with financial professionals and Istanbul Stock Market for over 26 years.

He is currently studying for his MSc in Computer Engineering at Bahcesehir University in the field of Big Data Analytics and Management.

KEY FEATURES

With increasing interest in AI around the world, deep learning has attracted a great deal of public attention. Every day, deep learning algorithms are used broadly across different industries. This book will give you a practical introduction to AI, including best practices using real-world use cases. You’ll learn to recognize and extract information to increase predictive accuracy and optimize results.

• Access 406 pages of digital content 24/7
• Get a practical deep dive into deep learning algorithms
• Explore deep learning further with Theano, Caffe, Keras, & TensorFlow
• Learn about two of the most powerful techniques at the core of many practical deep learning implementations: Auto-Encoders & Restricted Boltzmann Machines
• Dive into Deep Belief Nets & Deep Neural Networks
• Discover more deep learning algorithms with Dropout & Convolutional Neural Networks
• Get to know device strategies so you can use deep learning algorithms & libraries in the real world

PRODUCT SPECS

Details & Requirements

• Length of time users can access this course: lifetime
• Access options: web streaming, mobile streaming
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: all levels

Compatibility

• Internet required

THE EXPERT

Packt’s mission is to help the world put software to work in new ways, through the delivery of effective learning and information services to IT professionals. Working towards that vision, it has published over 4,000 books and videos so far, providing IT professionals with the actionable knowledge they need to get the job done–whether that’s specific learning on an emerging technology or optimizing key skills in more established tools.

KEY FEATURES

Designed to introduce you to the most relevant and powerful machine learning techniques used by today’s top data scientists, this book delivers clear examples and detailed code samples to demonstrate deep learning techniques, semi-supervised learning, and more. The techniques covered in this book are at the forefront of commercial practice and will help you break into this lucrative, growing industry.

• Compete w/ top data scientists by gaining a practical & theoretical understanding of cutting-edge deep learning algorithms
• Apply your new found skills to solve real problems
• Automate large sets of complex data & overcome time-consuming practical challenges
• Improve the accuracy of models & your existing input data using feature engineering techniques
• Use multiple learning techniques together to improve the consistency of results
• Understand the hidden structure of datasets using a range of unsupervised techniques
• Improve the effectiveness of your deep learning models further by using ensembling techniques to strap multiple models together

PRODUCT SPECS

Details & Requirements

• Length of time users can access this course: lifetime
• Access options: web streaming, mobile streaming
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: intermediate

Compatibility

• Internet required

THE EXPERT

Packt’s mission is to help the world put software to work in new ways, through the delivery of effective learning and information services to IT professionals. Working towards that vision, it has published over 3,000 books and videos so far, providing IT professionals with the actionable knowledge they need to get the job done–whether that’s specific learning on an emerging technology or optimizing key skills in more established tools.

KEY FEATURES

Apache Spark has become one of the most popular tools in machine learning because it can handle huge data sets at incredible speed. This book shows you Spark at its very best, demonstrating how to connect it with R to unlock maximum value from the tool and your data. These blueprints will reveal some of the most interesting challenges that Spark can help you tackle.

• Set up Apache Spark for machine learning and discover its impressive processing power
• Combine Spark & R to unlock detailed business insights essential for decision making
• Build machine learning systems w/ Spark that can detect fraud & analyze financial risks
• Create predictive models focusing on customer scoring & service ranking
• Design recommendation systems using SPSS on Apache Spark
• Tackle parallel computing & find out how it can support your machine learning projects
• Turn open data & communication data into actionable insights by making use of various forms of machine learning

PRODUCT SPECS

Details & Requirements

• Length of time users can access this course: lifetime
• Access options: web streaming, mobile streaming
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: intermediate

Compatibility

• Internet required

THE EXPERT

Packt’s mission is to help the world put software to work in new ways, through the delivery of effective learning and information services to IT professionals. Working towards that vision, it has published over 3,000 books and videos so far, providing IT professionals with the actionable knowledge they need to get the job done–whether that’s specific learning on an emerging technology or optimizing key skills in more established tools.

KEY FEATURES

Python is a general purpose and a relatively easy to learn programming language, making it the language of choice for data scientists to prototype, visualize, and run data analyses on small and medium-sized data sets. This book helps bridge the gap between machine learning and web development. You’ll focus on the Python language, frameworks, tools, and libraries, and eventually build a machine learning system.

• Get familiar w/ the fundamental concepts & some machine learning jargon
• Use tools & techniques to mine data from websites
• Grasp the core concepts of Django framework
• Get to know the most useful clustering & classification techniques and implement them in Python
• Acquire all the necessary knowledge to build a web application w/ Django
• Build & deploy a movie recommendation system application using the Django framework in Python

PRODUCT SPECS

Details & Requirements

• Length of time users can access this course: lifetime
• Access options: web streaming, mobile streaming
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: intermediate

Compatibility

• Internet required

THE EXPERT

Packt’s mission is to help the world put software to work in new ways, through the delivery of effective learning and information services to IT professionals. Working towards that vision, it has published over 3,000 books and videos so far, providing IT professionals with the actionable knowledge they need to get the job done–whether that’s specific learning on an emerging technology or optimizing key skills in more established tools.

KEY FEATURES

OpenCV is a library of programming functions mainly aimed at real-time computer vision. This course will show you how machine learning is a great choice to solve real-world computer vision problems and how you can use the OpenCV modules to implement popular machine learning concepts.

• Access 12 lectures & 1.5 hours of content 24/7
• Learn how to work w/ various OpenCV modules for statistical modeling & machine learning
• Discuss supervised & unsupervised learning, and how to implement them w/ real-world examples
• Implement efficient models using classification, regression, decision trees, K-nearest neighbors, & more

PRODUCT SPECS

Details & Requirements

• Length of time users can access this course: lifetime
• Access options: web streaming, mobile streaming
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: intermediate

Compatibility

• Internet required

THE EXPERT

Joe Minichino is a computer vision engineer for Hoolux Medical by day and a developer of the NoSQL database LokiJS by night. On weekends, he is a heavy metal singer/songwriter. He is a passionate programmer who is immensely curious about programming languages and technologies and constantly experiments with them. At Hoolux, Joe leads the development of an Android computer vision-based advertising platform for the medical industry.

Born and raised in Varese, Lombardy, Italy, and coming from a humanistic background in philosophy (at Milan’s Università Statale), Joe has spent his last 11 years living in Cork, Ireland, which is where he became a computer science graduate at the Cork Institute of Technology.

You can find him on LinkedIn at: https://www.linkedin.com/in/joeminichino

KEY FEATURES

TensorFlow is an open source software library for numerical computation using data flow graphs. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. This course addresses common commercial machine learning problems using Google’s TensorFlow library, familiarizing you with this powerful tool.

• Access 19 lectures & 1.5 hours of content 24/7
• Discover how to use TensorFlow & use it in real-world use cases
• Cover unique features like Data Flow Graphs, training, & visualization of performance w/ TensorBoard

PRODUCT SPECS

Details & Requirements

• Length of time users can access this course: lifetime
• Access options: web streaming, mobile streaming
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: all levels

Compatibility

• Internet required

THE EXPERT

Shams Ul Azeem is an undergraduate of NUST Islamabad, Pakistan, in Electrical Engineering. He has a great interest in the field of computer science and has started his journey from Android Development.Now he’s pursuing his career in Machine Learning, particularly in Deep Learning, by doing medical-related freelance projects with different companies.
He was also a member of RISE lab, NUST, and has a publication in the IEEE International Conference, ROBIO as a co-author on Designing of motions for humanoid goal keeper robots.

KEY FEATURES

Machine learning is transforming the way businesses operate, and being able to understand trends and patterns in complex data is becoming critical for success. Python can help you deliver key insights into your data by running unique algorithms and statistical models. Covering a wide range of powerful Python libraries, this book will get you up to speed with machine learning.

• Access 454 pages of content 24/7
• Find out how different machine learning techniques can be used to answer different data analysis questions
• Learn how to build neural networks using Python libraries & tools such as Keras & Theano
• Write clean & elegant Python code to optimize the strength of machine learning algorithms
• Discover how to embed your machine learning model in a web application
• Predict continuous target outcomes using regression analysis
• Uncover hidden patterns & structures in data w/ clustering

PRODUCT SPECS

Details & Requirements

• Length of time users can access this course: lifetime
• Access options: web streaming, mobile streaming
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: all levels

Compatibility

• Internet required

THE EXPERT

Packt’s mission is to help the world put software to work in new ways, through the delivery of effective learning and information services to IT professionals. Working towards that vision, it has published over 3,000 books and videos so far, providing IT professionals with the actionable knowledge they need to get the job done–whether that’s specific learning on an emerging technology or optimizing key skills in more established tools.

KEY FEATURES

Machine learning is pervasive in the modern, data-driven world. It’s used in search engines, robotic, self-driving cars, and many more instances. In this course, you’ll learn how to perform various machine learning tasks in many different environments. Focusing on real-life scenarios, you’ll learn how to solve real problems and use Python to implement algorithms.

• Access 97 lectures & 4.5 hours of content 24/7
• Deal w/ various types of data & explore the differences between machine learning paradigms
• Cover a range of regression techniques, classification algorithms, predictive modeling, & more
• Use real-world examples to solve real-life problems

PRODUCT SPECS

Details & Requirements

• Length of time users can access this course: lifetime
• Access options: web streaming, mobile streaming
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: all levels

Compatibility

• Internet required

THE EXPERT

Prateek Joshi is an artificial intelligence researcher, published author of five books, and TEDx speaker. He is the founder of Pluto AI, a venture-funded Silicon Valley startup building an analytics platform for smart water management powered by deep learning. His work in this field has led to patents, tech demos, and research papers at major IEEE conferences. He has been an invited speaker at technology and entrepreneurship conferences including TEDx, AT&T Foundry, Silicon Valley Deep Learning, and Open Silicon Valley. Prateek has also been featured as a guest author in prominent tech magazines.

His tech blog (www.prateekjoshi.com) has received more than 1.2 million page views from 200 over countries and has over 6,600+ followers. He frequently writes on topics such as artificial intelligence, Python programming, and abstract mathematics. He is an avid coder and has won many hackathons utilizing a wide variety of technologies. He graduated from University of Southern California with a master’s degree specializing in artificial intelligence. He has worked at companies such as Nvidia and Microsoft Research. You can learn more about him on his personal website at www.prateekj.com.

KEY FEATURES

Machine learning is the process of teaching machines to remember data patterns, use them to predict future outcomes, and offer choices that would appeal to individuals based on past preferences. Learning to build machine learning alogirthms within a controlled test framework will speed up your time to deliver, quantify quality expectations, and enabled rapid iteration and collaboration. This book will show you how to quantifiably test machine learning algorithms.

• Get started w/ an introduction to test-driven development & familiarize yourself with how to apply these concepts to machine learning
• Build & test a neural network deterministically, and learn to look for niche cases that cause odd model behavior
• Learn to use the multi-armed bandit algorithm to make optimal choices
• Generate complex & simple random data to create a wide variety of test cases
• Develop models iteratively, even when using a third-party library
• Quantify model quality to enable collaboration & rapid iteration
• Adopt simpler approaches to common machine learning algorithms
• Take behavior-driven development principles to articulate test intent

PRODUCT SPECS

Details & Requirements

• Length of time users can access this course: lifetime
• Access options: web streaming, mobile streaming
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: all levels

Compatibility

• Internet required

THE EXPERT

Packt’s mission is to help the world put software to work in new ways, through the delivery of effective learning and information services to IT professionals. Working towards that vision, it has published over 3,000 books and videos so far, providing IT professionals with the actionable knowledge they need to get the job done–whether that’s specific learning on an emerging technology or optimizing key skills in more established tools.

KEY FEATURES

Data science and machine learning are some of the top buzzwords in the tech world today. This course is your entry point to machine learning! More companies than ever are relying on data mining to make informed business decisions and data scientists are in increasing demand. This course will put you on track for a lucrative career in Big Data.

• Access 45 lectures & 5 hours of content 24/7
• Get an introduction to machine learning & the Python language
• Learn important concepts like exploratory data analysis, data preprocessing, feature extraction, classification, & more
• Acquire the mechanics of several important machine learning algorithms
• Gather a broad picture of the machine learning ecosystem & master best practices
• Tackle data-driven problems & implement your solutions w/ Python

PRODUCT SPECS

Details & Requirements

• Length of time users can access this course: lifetime
• Access options: web streaming, mobile streaming
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: all levels

Compatibility

• Internet required

THE EXPERT

Yuxi (Hayden) Liu is currently a data scientist working on messaging app optimization at a multinational online media corporation in Toronto. He focuses on social graph mining, user demographics, interest prediction, spam detection, and recommendation systems. He has worked for several years as a data scientist in real-time bidding programmatic advertising, where he applied his machine learning expertise in ad optimization, click-through rate and conversion prediction, and click fraud detection. Hayden earned his degree from the University of Toronto, and published five IEEE transactions and conference papers during his master’s research. He is also a machine learning education enthusiast, and has authored the Python Machine Learning By Example book.

KEY FEATURES

Large Python machine learning projects involve new problems associated with specialized machine learning architectures and designs that many data scientists have yet to tackle. But finding algorithms and designing and building platforms that deal with large data sets is a growing need. This course uncovers a new wave of machine learning algorithms that meet scalability demands together with a high predictive accuracy.

• Apply the most scalable machine learning algorithms
• Work w/ modern state-of-the-art large-scale machine learning techniques
• Increase predictive accuracy w/ deep learning & scalable data-handling techniques
• Improve your work by combining the MapReduce framework w/ Spark
• Build powerful ensembles at scale
• Use data streams to train linear & non-linear predictive models from extremely large datasets using a single machine

PRODUCT SPECS

Details & Requirements

• Length of time users can access this course: lifetime
• Access options: web streaming, mobile streaming
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: all levels

Compatibility

• Internet required

THE EXPERT

Packt’s mission is to help the world put software to work in new ways, through the delivery of effective learning and information services to IT professionals. Working towards that vision, it has published over 3,000 books and videos so far, providing IT professionals with the actionable knowledge they need to get the job done–whether that’s specific learning on an emerging technology or optimizing key skills in more established tools.

KEY FEATURES

Course Description

Your programming toolbox wouldn’t be complete without Python. Whether you’re looking to work in data analysis, machine learning, or web development, this course walks you through using Python to solve a myriad of programming problems. You’ll dive into Python loops, data structures, functions, and more to help you perform basic programming tasks and confidently apply those skills to real-world scenarios.

• Access 28 lectures & 3 hours of content 24/7
• Get started w/ zero Python experience
• Enhance your understanding of loops, data structures, functions & classes
• Explore popular Python libraries & Web scraping
• Discover what it takes to write a real Python app

PRODUCT SPECS

Important Details

• Length of time users can access this course: lifetime
• Access options: web
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: beginner

Requirements

• Internet required

THE EXPERT

Instructor

Loonycorn is comprised of a couple of individuals —Janani Ravi and Vitthal Srinivasan—who have honed their tech expertise at Google and Stanford. The team believes it has distilled the instruction of complicated tech concepts into funny, practical, engaging courses, and is excited to be sharing its content with eager students.

KEY FEATURES

Course Description

Work as a deep learning developer would be infinitely harder without TensorFlow. Created by Google in 2015, this open-source software library makes it easier for developers to design, build, and train deep learning models. Using TensorFlow, this course will guide you through Convolutional Neural Networks and Recurrent Neural Networks, cutting-edge tools in image recognition, language modeling, and working with high-frequency data.

• Access 28 lectures & 3.5 hours of content 24/7
• Use TensorFlow to work w/ convolutional & recurrent neural networks
• Learn how neural networks contribute to image recognition & language modeling
• Explore real-world deep learning examples via lab lessons

PRODUCT SPECS

Important Details

• Length of time users can access this course: lifetime
• Access options: web
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: all levels

Requirements

• Internet required

THE EXPERT

Instructor

Loonycorn is comprised of a couple of individuals —Janani Ravi and Vitthal Srinivasan—who have honed their tech expertise at Google and Stanford. The team believes it has distilled the instruction of complicated tech concepts into funny, practical, engaging courses, and is excited to be sharing its content with eager students.

KEY FEATURES

Course Description

Deep learning has allowed today’s AI applications to do some amazing things, but only the Cloud has enough computing firepower to keep these programs running. This course will guide you through running deep learning models in TensorFlow on the Google Cloud platform. You’ll explore building and deploying TensorFlow models and apply your skills to the real world with a taxicab fare prediction problem.

• Access 30 lectures & 3 hours of content 24/7
• Learn how to build & deploy TensorFlow models on Google Cloud
• Refine your training w/ real-world labs, like a taxicab fare prediction problem
• Explore feature engineering & hyperparameter tuning

PRODUCT SPECS

Important Details

• Length of time users can access this course: lifetime
• Access options: web
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: basic

Requirements

• Internet required

THE EXPERT

Instructor

Loonycorn is comprised of a couple of individuals —Janani Ravi and Vitthal Srinivasan—who have honed their tech expertise at Google and Stanford. The team believes it has distilled the instruction of complicated tech concepts into funny, practical, engaging courses, and is excited to be sharing its content with eager students.

KEY FEATURES

Course Description

Unsupervised deep learning might sound chaotic, but there’s a method to the madness. While supervised deep learning hinges on the programmer telling the program which insights to find, unsupervised deep learning allows the machine to gather insights on its own, making for unique—and sometimes game-changing—discoveries. Make your way through this training, and you’ll explore the theory of unsupervised deep learning and implement models in TensorFlow.

• Access 22 lectures & 2.5 hours of content 24/7
• Discover how to implement unsupervised deep learning models w/ TensorFlow
• Learn the advantages of supervised versus unsupervised deep learning
• Explore K-means clustering w/ images
• Understand how to create & work on a datalab instance

PRODUCT SPECS

Important Details

• Length of time users can access this course: lifetime
• Access options: web
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: basic

Requirements

• Internet required

THE EXPERT

Instructor

Loonycorn is comprised of a couple of individuals —Janani Ravi and Vitthal Srinivasan—who have honed their tech expertise at Google and Stanford. The team believes it has distilled the instruction of complicated tech concepts into funny, practical, engaging courses, and is excited to be sharing its content with eager students.

KEY FEATURES

Course Description

Deep learning isn’t just about helping computers learn from data—it’s about helping those machines determine what’s important in those datasets. This is what allows for Tesla’s Model S to drive on its own and for Siri to determine where the best brunch spots are. Using the machine learning workhorse that is TensorFlow, this course will show you how to build deep learning models and explore advanced AI capabilities with neural networks.

• Access 62 lectures & 8.5 hours of content 24/7
• Understand the anatomy of a TensorFlow program & basic constructs such as graphs, tensors, and constants
• Create regression models w/ TensorFlow
• Learn how to streamline building & evaluating models w/ TensorFlow’s estimator API
• Use deep neural networks to build classification & regression models

PRODUCT SPECS

Important Details

• Length of time users can access this course: lifetime
• Access options: web
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: intermediate

Requirements

• Internet required

THE EXPERT

Instructor

Loonycorn is comprised of a couple of individuals —Janani Ravi and Vitthal Srinivasan—who have honed their tech expertise at Google and Stanford. The team believes it has distilled the instruction of complicated tech concepts into funny, practical, engaging courses, and is excited to be sharing its content with eager students.

KEY FEATURES

Course Description

From suggested Facebook friends to recommended videos on Netflix, it’s scary how accurate these systems can be; but they’re not powered by magic. This course peels back the curtain on the technology that drives these programs. Using Python, you’ll discover what goes into designing and implementing recommendation systems and explore the different ways they curate content.

• Access 20 lectures & 4 hours of content 24/7
• Identify use-cases for recommendation systems
• Design & implement recommendation systems in Python
• Discover the different means of filtering content

PRODUCT SPECS

Important Details

• Length of time users can access this course: lifetime
• Access options: web
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: basic

Requirements

• Internet required

THE EXPERT

Instructor

Loonycorn is comprised of a couple of individuals —Janani Ravi and Vitthal Srinivasan—who have honed their tech expertise at Google and Stanford. The team believes it has distilled the instruction of complicated tech concepts into funny, practical, engaging courses, and is excited to be sharing its content with eager students.

KEY FEATURES

Course Description

If you’re at all interested in the technology that powers Siri, self-driving cars, and other AI innovations, you’ll need to get comfortable with machine learning. This course features training from Silicon Valley pros with decades of experience under their belts. Even if you’ve never touched a line of code before, these experts will help you put Machine Learning and Python into action and harness a new level of programming power.

• Access 38 lectures & 8.5 hours of content 24/7
• Get introduced to Machine Learning
• Learn from a team w/ decades of practical experience in quant trading, analytics & e-commerce
• Understand complex programming subjects w/ the help of animations
• Discover how to implement natural language processing & machine learning for text classification in Python

PRODUCT SPECS

Important Details

• Length of time users can access this course: lifetime
• Access options: web
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: basic

Requirements

• Internet required

THE EXPERT

Instructor

Loonycorn is comprised of a couple of individuals —Janani Ravi and Vitthal Srinivasan—who have honed their tech expertise at Google and Stanford. The team believes it has distilled the instruction of complicated tech concepts into funny, practical, engaging courses, and is excited to be sharing its content with eager students.

KEY FEATURES

Course Description

Classification models play a key role in helping computers accurately predict outcomes, like when a banking program identifies loan applicants as low, medium, or high credit risks. This course offers an overview of machine learning with a focus on implementing classification models via Python’s scikit-learn. If you’re an aspiring developer or data scientist looking to take your machine learning knowledge further, this course is for you.

• Access 17 lectures & 2 hours of content 24/7
• Tackle basic machine learning concepts, including supervised & unsupervised learning, regression, and classification
• Learn about support vector machines, decision trees & random forests using real data sets
• Discover how to use decision trees to get better results

PRODUCT SPECS

Important Details

• Length of time users can access this course: lifetime
• Access options: web
• Certification of completion not included
• Redemption deadline: redeem your code within 30 days of purchase
• Experience level required: basic

Requirements

• Internet required

THE EXPERT

Instructor

Loonycorn is comprised of a couple of individuals —Janani Ravi and Vitthal Srinivasan—who have honed their tech expertise at Google and Stanford. The team believes it has distilled the instruction of complicated tech concepts into funny, practical, engaging courses, and is excited to be sharing its content with eager students.