by Roland Meertens | Released February 2018 | ISBN: 9781788622752

Get hands-on and understand Advanced Neural Networks with TensorFlowAbout This VideoAn Extensive course to build advanced neural networks in TensorFlow.Implement different networks with practical examplesSolve common Neural Network problems with TensorFlow.In DetailNeural Networks are at the forefront of almost all recent major technology breakthroughs. The intersection of big data, parallel programming, and AI generated a new wave of Neural Network research. In this course, you will be taken through some of the best uses of Neural Networks using TensorFlow.You'll explore Deep Reinforcement Learning algorithms such as Generative Networks and Deep Q Learning. You will learn to implement some more complex types of neural networks such as Deep Q Learning with OpenAI Gym, autoencoders, and Siamese neural networks. During the course of the video, you will be working on real-world datasets to get a hands-on understanding of neural network programming. You will also get to train generative models and will learn Autoencoder applications.By the end of this course, you will have a fair understanding of how you can leverage the power of TensorFlow to train neural networks of varying complexities, without any hassle. Show and hide more

1. Chapter 1 : ChapterName
   • The Course Overview 00:03:52
   • The Approach of This Course 00:02:51
   • Installing Docker and Downloading the Source Code for This Course 00:08:06
   • Understanding Jupyter Notebooks and TensorFlow 00:12:56
2. Chapter 2 : ChapterName
   • Visualizing Your Graph 00:07:08
   • Adding Summaries 00:08:58
   • Plotting the Weights in a Histogram 00:09:42
   • Inspecting Input and Output 00:06:16
3. Chapter 3 : ChapterName
   • Encoding MNIST Characters 00:12:40
   • Practical Application –Denoising 00:06:21
   • The Dropout Layer 00:08:42
   • Variational Autoencoders 00:11:32
4. Chapter 4 : ChapterName
   • The Omniglot Dataset 00:09:14
   • What Is a Siamese Neural Network? 00:06:56
   • Training and Testing a Siamese Neural Network 00:05:59
   • Alternative Loss Functions 00:06:39
   • Speed of Your Network 00:13:29
5. Chapter 5 : ChapterName
   • Getting Started with the OpenAI Gym 00:09:31
   • Random Search 00:08:41
   • Reinforcement Learning Explained 00:06:34
   • Reinforcement Learning Explained (Continued) 00:11:17
   • Reinforcement Learning Tricks 00:08:03
   • Playing Atari Games 00:10:46
   • Defining Our Network 00:06:37
   • Starting and Training a Session 00:10:48
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