by Alvaro Fuentes | Released June 2018 | ISBN: 9781788623209

Recipes for Computer vision, Natural Language Processing, Reinforcement Learning, Finance, and moreAbout This VideoLearn how to build models to solve problems in Computer vision, Natural Language Processing, Reinforcement Learning, Finance, and moreA hands-on approach to the most exciting applications of Deep LearningUnderstand how to build advanced Deep Learning models with TensorFlowIn DetailThis course is all about some of the most exciting applications of Deep Learning and how to implement them in TensorFlow. You will learn how to build models to solve problems in different domains such as Computer vision, Natural Language Processing, Reinforcement Learning, Finance, and more.Taking a Cookbook approach, this course presents you with easy-to-follow recipes to show the use of advanced Deep Learning techniques and their implementation in TensorFlow. After taking this tutorial you will be able to start building advanced Deep Learning models with TensorFlow for applications with a wide range of fields.All the code and supporting files for this course are available on Github at https://github.com/PacktPublishing/-TensorFlow-1.X-Deep-Learning-Recipes-for-Artificial-Intelligence-Applications-v- Show and hide more

1. Chapter 1 : Convolutional Neural Networks for Computer Vision
   • The Course Overview 00:04:12
   • Installation and Setup 00:08:30
   • Defining Layers for Image Recognition 00:12:54
   • Building an Image Classifier with CNNs 00:11:14
   • Building Better CNNs with Regularization 00:05:10
   • Transfer Learning 00:13:43
2. Chapter 2 : Applications of Recurrent Neural Networks
   • The Intuition Behind RNNs 00:11:07
   • Time Series Forecasting with RNN 00:10:10
   • Producing Word Embeddings for NLP Tasks 00:11:57
   • Processing Text Sequences with LSTM Networks 00:10:33
3. Chapter 3 : Application of Deep Learning to AI Problems
   • Guessing Correlations from Scatter Plots 00:12:58
   • Introduction to Generative Adversarial Networks 00:08:55
   • Creating Images with GANs 00:15:02
   • Sequence to Sequence Models 00:06:06
   • Building a Language Translator 00:13:49
4. Chapter 4 : Introduction to Reinforcement Learning
   • Key Concepts in Reinforcement Learning 00:07:59
   • A Simple Environment and Basic Policies 00:08:29
   • Training a Neural Network Policy 00:08:42
   • Using an Intelligent Agent 00:03:41
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