Tag Archive: Learning

KEY FEATURES

Ansible is an open source automation platform that assists organizations with tasks such as configuration management, application deployment, orchestration, and task automation. In this book, you’ll learn about the fundamentals and practical aspects of Ansible 2, getting accustomed to new features and learning how to integrate with cloud platforms like Amazon Web Services. By the end, you’ll be able to leverage Ansible parameters to expedite tasks for your organization. Or yourself.

• Access 240 pages of content 24/7
• Set up Ansible 2 & an Ansible 2 project in a future-proof way
• Perform basic operations w/ Ansible 2 such as creating, copying, moving, changing, & deleting files
• Deploy complete cloud environments using Ansible 2 on AWS & DigitalOcean
• Explore complex operations w/ Ansible 2
• Develop & test Ansible playbooks
• Write a custom module & test it

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

DevOps is a practical field that focuses on delivering business value as efficiently as possible. DevOps encompasses all the flows from code through testing environments to production environments, stressing cooperation between different roles and how they can work together more closely. Through this book, you’ll learn how DevOps affects architecture, starting by creating a sample enterprise Java application that you will continue to work with throughout the following chapters.

• Access 240 pages of content 24/7
• Understand how all DevOps systems fit together to form a larger whole
• Set up & familiarize yourself w/ all the tools you need to be efficient w/ DevOps
• Design an application that is suitable for continuous deployment systems
• Store & manage your code effectively using different options such as Git, Gerrit, & Gitlab
• Configure a job to build a sample CRUD application
• Test the code using automated regression testing w/ Jenkins Selenium
• Deploy your code using tools such as Puppet, Ansible, Palletops, Chef, & Vagrant
• Monitor the health of your code w/ Nagios, Munin, & Graphite

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

There has been a recent explosion in tools that allow you to redefine the delivery of infrastructure and applications, using a combination of automation and testing to deliver continuous deployment. This book shows you how to use some of the newest and most exciting tools to revolutionize the way you deliver applications and software. By tackling real-world issues, you’ll be guided through a huge variety of tools.

• Access 334 pages of content 24/7
• Manage, use, & work w/ code in the Git version management system
• Create hosts automatically using a simple combination of TFTP, DHCP, & pre-seeds
• Implement virtual hosts using the ubiquitous VMware ESXi hypervisor
• Control configuration using Ansible
• Develop powerful, consistent, & portable containers using Docker
• Track trends, discover data, & monitor key systems using InfluxDB, syslog, & Sensu
• Deal efficiently w/ powerful cloud infrastructures using AWS Infrastructure & the Heroku Platform as services

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 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

The Python programming language, beyond having conquered the scientific community in the last decade, is now an indispensable tool for data scientists. Using Python will offer you a fast, reliable, cross-platform, and mature environment for data analysis, machine learning, and algorithmic problem solving. This comprehensive guide will help you move beyond the hype and transcend the theory by providing you with a hands-on, advanced study of data science.

• Access 294 pages of content 24/7
• Manage data & perform linear algebra in Python
• Derive inferences from the analysis by performing inferential statistics
• Solve data science problems in Python
• Create high-end visualizations using Python
• Evaluate & apply the linear regression technique to estimate the relationships among variables
• Build recommendation engines w/ the various collaborative filtering algorithms
• Apply ensemble methods to improve your predictions

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 analysis is more important in business than ever and data scientists are getting paid the big bucks to help companies make better informed decisions. This book explains basic data algorithms using hands-on machine learning techniques. You’ll perform data-driven innovation processing for several types of data such as text, images, social network graphs, documents, and more.

• Access 338 pages of content 24/7
• Acquire, format, & visualize your data
• Build an image-similarity search engine
• Generate meaningful visualizations that anyone can understand
• Get started w/ analyzing social network graphs
• Find out how to implement sentiment text analysis
• Install data analysis tools such as Pandas, MongoDB, & Apache Spark
• Implement machine learning algorithms such as classification or forecasting

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

Every business wants to gain insights from data to make more informed decisions. Data mining provides a way of finding these insights, and Python is one of the most popular languages with which to perform it. In this course, you will discover the key concepts of data mining and learn how to apply different techniques to gain insight to real-world data. By course’s end, you’ll have a valuable skill that companies are clamoring to hire for.

• Access 21 lectures & 2 hours of content 24/7
• Discover data mining techniques & the Python libraries used for data mining
• Tackle notorious data mining problems to get a concrete understanding of these techniques
• Understand the process of cleaning data & the steps involved in filtering out noise
• Build an intelligent application that makes predictions from data
• Learn about classification & regression techniques like logistic regression, k-NN classifier, & mroe
• Predict house prices & the number of TV show viewers

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

Saimadhu Polamuri is a data science educator and the founder of Data Aspirant, a Data Science portal for beginners. He has 3 years of experience in data mining and 5 years of experience in Python. He is also interested in big data technologies such as Hadoop, Pig, and Spark. He has a good command of the R programming language and Matlab. He has a rudimentary understanding of Cpp Computer vision library (opencv) and big data technologies.

KEY FEATURES

Machine learning gives you extremely powerful insights into data, and has become so ubiquitous you see it nearly constantly while you browse the internet without even knowing it. Implementations of machine learning are as diverse as recommendation systems to self-driving cars. In this course, you’ll be introduced to a unique blend of projects that will teach you what machine learning is all about and how you can use Python to create machine learning projects.

• Access 26 lectures & 3 hours of content 24/7
• Work on six independent projects to help you master machine learning in Python
• Cover concepts such as classification, regression, clustering, & more
• Apply various machine learning algorithms
• Master Python’s packages & libraries to facilitate computation
• Implement your own machine learning models

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

Alexander T. Combs is an experienced data scientist, strategist, and developer with a background in financial data extraction, natural language processing and generation, and quantitative and statistical modeling. He is currently a full-time lead instructor for a data science immersive program in New York City.

KEY FEATURES

Machine learning, artificial intelligence, and robotics are flying into the mainstream, but these advanced technologies have been creeping into our everyday lives for awhile now. Machine learning and AI are used regularly in data security, healthcare, financial trading, and more. In recent years, we’ve seen self-driving cars become one of the greatest technological frontiers. In this course, you’ll learn the robotics fundamentals and machine learning concepts that apply to self-driving cars. All you need is just a little algebra.

• Access 82 lectures & 20 hours of content 24/7
• Get started w/ Python
• Learn supervised & unsupervised learning techniques
• Discuss linear regression, artificial neural networks, & Support Vector Machine (SVM)
• Work w/ actuators, sensors, & batteries
• Understand how to work w/ microcontrollers & Arduino

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

With the call by President Obama to update the national US. cybersecurity strategy in order to help secure the United States in cyberspace, all the different goals set by this initiative cannot be achieved without experienced security professionals, able to dissect, stop and prevent sophisticated cyber attacks. This is the mission of CyberTraining 365, prepare security professionals worldwide to help to secure their nations against organized crime.

CyberTraining 365 main focus is to prepare professionals with the best techniques to defend their organizations at all different layers: In the perimeter, internal network, applications, memory and binary level.

We offer multiple certifications taught by authors of Gray Hat Hacking book and Certified EC-Council Instructors who have experience in real state-sponsored attacks worldwide. Our courses are aligned with the National Cybersecurity Workforce Framework developed by National Initiative for Cybersecurity Education (NICE).

Our career path starts from 101 courses for new security professionals but goes all the way up to Advanced courses for experienced ethical hackers, including the best security tools in the Market that are not accessible for students due to its high cost.

Our online academy is unique in the world, with a social network with multiple students interacting online, with CTF-like challenges released constantly to test the students skills which give them points that are reflected in the ranking system showing the best minds in the Academy and finally with head hunters monitoring the best students throwing them job offers daily.

Do you want to compete with other professionals to know who is the best Penetration Tester, Malware Analysis or Reverse Engineer while learning real-world attack and defense techniques? Come and show us what you got!

For more details on this course and instructor, click here.

KEY FEATURES

If your dream is to master a foreign language, there’s not better teacher than Rosetta Stone. With its intuitive, immersive method, Rosetta Stone will have you reading, writing, and speaking like a natural in no time. You’ll start by matching words with images just like when you learned your native language as a child. Then you’ll move onto interactive lessons where speech recognition technology works to evaluate and improve your accent with instant feedback. The reviews don’t lie, Rosetta Stone is the best way to master a second, third, or fourth language from home.

PC Magazine Editors’ Choice Award: Best Language-Learning Software

“Rosetta Stone TOTALe may be the next best thing to living in a country.” Wall Street Journal

• Learn a new language w/ the award-winning interactive software & proprietary speech-recognition technology that analyzes the words you say 100 times per second
• Develop your command of the language–read, write, speak & understand
• Learn basic conversational skills like shopping, ordering, taking a taxi, etc.
• Move onto advanced language skills like sharing opinions & discussing pop culture
• Enhance your learning on-the-go w/ Rosetta Stone mobile apps (3-month trial included)
• Take levels 1-5 to go from beginner to advanced
• Use the advanced speech engine to compare your accent to native speakers
• Get 12 live tutoring sessions w/ a native speaker

PRODUCT SPECS

Details & Requirements

• Includes access for up to 5 family members, 2 computers
• Learn at your own pace – this course that never expires!

Compatibility

• Windows 2000 or later
• Mac OS X 10.4.11 or later
• 1 GHz or faster CPU
• 512 MB RAM
• 600 MB free hard-drive space (per level)
• Internet or phone connection for activation
• Only available to residents of the United States, Australia, Europe, Brazil, Argentina, China, India, and Mexico.

Includes

• Rosetta Stone, US English Levels 1-5
• Serial code for digital download of product
• 90-day access to mobile language learning product

KEY FEATURES

Machine learning gives you extremely powerful insights into data, and has become so ubiquitous you see it nearly constantly while you browse the internet without even knowing it. Implementations of machine learning are as diverse as recommendation systems to self-driving cars. In this course, you’ll be introduced to a unique blend of projects that will teach you what machine learning is all about and how you can use Python to create machine learning projects.

• Access 26 lectures & 3 hours of content 24/7
• Work on six independent projects to help you master machine learning in Python
• Cover concepts such as classification, regression, clustering, & more
• Apply various machine learning algorithms
• Master Python’s packages & libraries to facilitate computation
• Implement your own machine learning models

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

Alexander T. Combs is an experienced data scientist, strategist, and developer with a background in financial data extraction, natural language processing and generation, and quantitative and statistical modeling. He is currently a full-time lead instructor for a data science immersive program in New York City.

KEY FEATURES

Machine learning, artificial intelligence, and robotics are flying into the mainstream, but these advanced technologies have been creeping into our everyday lives for awhile now. Machine learning and AI are used regularly in data security, healthcare, financial trading, and more. In recent years, we’ve seen self-driving cars become one of the greatest technological frontiers. In this course, you’ll learn the robotics fundamentals and machine learning concepts that apply to self-driving cars. All you need is just a little algebra.

• Access 82 lectures & 20 hours of content 24/7
• Get started w/ Python
• Learn supervised & unsupervised learning techniques
• Discuss linear regression, artificial neural networks, & Support Vector Machine (SVM)
• Work w/ actuators, sensors, & batteries
• Understand how to work w/ microcontrollers & Arduino

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

With the call by President Obama to update the national US. cybersecurity strategy in order to help secure the United States in cyberspace, all the different goals set by this initiative cannot be achieved without experienced security professionals, able to dissect, stop and prevent sophisticated cyber attacks. This is the mission of CyberTraining 365, prepare security professionals worldwide to help to secure their nations against organized crime.

CyberTraining 365 main focus is to prepare professionals with the best techniques to defend their organizations at all different layers: In the perimeter, internal network, applications, memory and binary level.

We offer multiple certifications taught by authors of Gray Hat Hacking book and Certified EC-Council Instructors who have experience in real state-sponsored attacks worldwide. Our courses are aligned with the National Cybersecurity Workforce Framework developed by National Initiative for Cybersecurity Education (NICE).

Our career path starts from 101 courses for new security professionals but goes all the way up to Advanced courses for experienced ethical hackers, including the best security tools in the Market that are not accessible for students due to its high cost.

Our online academy is unique in the world, with a social network with multiple students interacting online, with CTF-like challenges released constantly to test the students skills which give them points that are reflected in the ranking system showing the best minds in the Academy and finally with head hunters monitoring the best students throwing them job offers daily.

Do you want to compete with other professionals to know who is the best Penetration Tester, Malware Analysis or Reverse Engineer while learning real-world attack and defense techniques? Come and show us what you got!

For more details on this course and instructor, click here.

KEY FEATURES

Deep Learning is a set of powerful algorithms that are the force behind self-driving cars, image searching, voice recognition, and many, many more applications we consider decidedly “futuristic.” One of the central foundations of deep learning is linear regression; using probability theory to gain deeper insight into the “line of best fit.” This is the first step to building machines that, in effect, act like neurons in a neural network as they learn while they’re fed more information. In this course, you’ll start with the basics of building a linear regression module in Python, and progress into practical machine learning issues that will provide the foundations for an exploration of Deep Learning.

• Access 20 lectures & 2 hours of content 24/7
• Use a 1-D linear regression to prove Moore’s Law
• Learn how to create a machine learning model that can learn from multiple inputs
• Apply multi-dimensional linear regression to predict a patient’s systolic blood pressure given their age & weight
• Discuss generalization, overfitting, train-test splits, & other issues that may arise while performing data analysis

Like what you’re learning? Try out the The Advanced Guide to Deep Learning and Artificial Intelligence next.

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 you must have some knowledge of calculus, linear algebra, probability, Python, and Numpy
• All code for this course is available for download here, in the directory linear_regression_class

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

Logistic regression is one of the most fundamental techniques used in machine learning, data science, and statistics, as it may be used to create a classification or labeling algorithm that quite resembles a biological neuron. Logistic regression units, by extension, are the basic bricks in the neural network, the central architecture in deep learning. In this course, you’ll come to terms with logistic regression using practical, real-world examples to fully appreciate the vast applications of Deep Learning.

• Access 31 lectures & 3 hours of content 24/7
• Code your own logistic regression module in Python
• Complete a course project that predicts user actions on a website given user data
• Use Deep Learning for facial expression recognition
• Understand how to make data-driven decisions

Like what you’re learning? Try out the The Advanced Guide to Deep Learning and Artificial Intelligence next.

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 you must have some knowledge of calculus, linear algebra, probability, Python, and Numpy
• All code for this course is available for download here, in the directory logistic_regression_class

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

Artificial neural networks are the architecture that make Apple’s Siri recognize your voice, Tesla’s self-driving cars know where to turn, Google Translate learn new languages, and so many more technological features you have quite possibly taken for granted. The data science that unites all of them is Deep Learning. In this course, you’ll build your very first neural network, going beyond basic models to build networks that automatically learn features.

• Access 37 lectures & 4 hours of content 24/7
• Extend the binary classification model to multiple classes uing the softmax function
• Code the important training method, backpropagation, in Numpy
• Implement a neural network using Google’s TensorFlow library
• Predict user actions on a website given user data using a neural network
• Use Deep Learning for facial expression recognition
• Learn some of the newest development in neural networks

Like what you’re learning? Try out the The Advanced Guide to Deep Learning and Artificial Intelligence next.

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, but you must have some knowledge of calculus, linear algebra, probability, Python, and Numpy
• All code for this course is available for download here, in the directory ann_class

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

The applications of Deep Learning are many, and constantly growing, just like the neural networks that it supports. In this course, you’ll delve into advanced concepts of Deep Learning, starting with the basics of TensorFlow and Theano, understanding how to build neural networks with these popular tools. Using these tools, you’ll learn how to build and understand a neural network, knowing exactly how to visualize what is happening within a model as it learns.

• Access 23 lectures & 3 hours of programming 24/7
• Discover batch & stochastic gradient descent, two techniques that allow you to train on a small sample of data at each iteration, greatly speeding up training time
• Discuss how momentum can carry you through local minima
• Learn adaptive learning rate techniques like AdaGrad & RMSprop
• Explore dropout regularization & other modern neural network techniques
• Understand the variables & expressions of TensorFlow & Theano
• Set up a GPU-instance on AWS & compare the speed of CPU vs GPU for training a deep neural network
• Look at the MNIST dataset & compare against known benchmarks

Like what you’re learning? Try out the The Advanced Guide to Deep Learning and Artificial Intelligence next.

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 you must have some knowledge of calculus, linear algebra, probability, Python, and Numpy
• All code for this course is available for download here, in the directory ann_class2

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.