by Saikat Basak | Released March 2018 | ISBN: 9781789135091

A practical approach to deep learning and deep reinforcement learning for building real-world applications using TensorFlowAbout This VideoState-of-the-art AI algorithmsA hands-on approach to problem-solving.You'll have a practical, working project after completing every sectionIn DetailTensorFlow is one of the most commonly used frameworks for Deep Learning and AI. This course will be your guide to understand and learn the concepts of Artificial intelligence by applying them in a real-world project with TensorFlow. This course will show you how to combine the power of Artificial Intelligence and TensorFlow to develop some exciting applications for the real world. This course will take you through all the relevant AI domains, tools, and algorithms required to build optimal solutions and will show you how to implement them hands-on. You will then be taken through techniques such as reinforcement learning, heuristic searches, neural networks, Computer Vision, OpenAI Gym, and more in different stages of your application. This course will show you how to implement AI practically using TensorFlow models and how it eases the way you interact with the technology. You will learn how TensorFlow can be used to analyze a variety of data sets and will learn to optimize various AI algorithms. By the end of the course, you will have learned to build intelligent apps by leveraging the full potential of Artificial Intelligence with TensorFlow.All the code and supporting files for this course are available on Github at https://github.com/PacktPublishing/Hands-on-Artificial-Intelligence-with-TensorFlow Show and hide more

1. Chapter 1 : Fired Up, Ready to Go.
   • The Course Overview 00:02:27
   • The Current State of Artificial Intelligence 00:02:47
   • Setting Up the Environment for Deep Learning 00:04:17
2. Chapter 2 : Deep Learning for Computer Vision
   • Deep Learning in Fashion 00:11:19
   • An Intro to Transfer Learning: Skin Cancer Classification 00:07:19
   • Fundamentals of Object Localization and Detection 00:07:24
   • YOLO(You only look once): Single Shot Object Detection 00:14:39
3. Chapter 3 : Adversarial Learning in Application
   • Unravelling Adversarial Learning and Generative Adversarial Nets 00:07:28
   • Generating Handwritten Digits Using GANs 00:06:03
   • Generating New Pokemons Using a DCGAN 00:05:43
   • Super-Resolution Generative Adversarial Networks 00:05:45
4. Chapter 4 : Deep Reinforcement Learning for Game AI
   • Setting Up OpenAI Gym 00:01:30
   • Introduction to Reinforcement Learning 00:03:08
   • Simple Q-Learning: Building Our First Video Game Bot 00:06:04
   • Deep Q-Learning: Building a Game Bot that Plays the Classic Atari Games 00:05:50
   • Deep Reinforcement Learning with Policy Gradient - AI that Plays Pong 00:04:28
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