by Giuseppe Ciaburro, Nimish Narang | Released April 2019 | ISBN: 9781838648909

Leverage the power of Keras to build and train state-of-the-art deep learning modelsAbout This VideoStudy the Keras architecture and its different models in detailLearn to solve time series regression issues with recurrent neural networksUnderstand and use reinforcement learning to control a mechanical systemIn DetailKeras is a Python library that provides a simple and clean way to create a range of deep learning models. This course introduces you to Keras and shows you how to create applications with maximum readability.You take your first steps by getting introduced to Keras, its benefits, and its applications. As you get comfortable with Keras, you will learn how to predict business outcomes using time series data and various forecasting techniques. By learning the basic concepts of reinforcement learning, you will be able to create algorithms that can learn and adapt to environmental changes and control your robots. Then, you will learn various natural language processing techniques and use the Natural Language Toolkit to analyze, classify, and tag text.By the end of the course, you'll have the skills and the confidence to work on existing deep learning projects or create your own applications.The code bundle for this course can be downloaded from here: https://github.com/TrainingByPackt/Keras-2.X-Projects-eLearning Show and hide more

1. Chapter 1 : Getting Started with Keras
   • Course Overview 00:02:57
   • Installation and Setup 00:09:59
   • Lesson Overview 00:01:27
   • Introduction to Keras 00:05:28
   • Keras Backend Options 00:13:14
   • Model Fitting in Keras 00:04:16
   • The Keras Sequential Model Architecture 00:13:28
   • Keras Functional API Model Architecture 00:08:23
   • Lesson Summary 00:01:03
2. Chapter 2 : Stock Volatility Forecasting Using Long Short-Term Memory
   • Lesson Overview 00:02:21
   • The Basics of Forecasting 00:07:56
   • Time Series Analysis 00:11:21
   • Time Series Models 00:05:47
   • Long Short-Term Memory (LSTM) in Keras 00:09:14
   • Implementing an LSTM to Forecast Stock Volatility 00:19:39
   • Data Scaling 00:07:57
   • Keras LSTM Model 00:27:19
   • Lesson Summary 00:01:13
3. Chapter 3 : Robot Control System Using Deep Reinforcement Learning
   • Lesson Overview 00:01:29
   • Robot Control Overview 00:12:15
   • The Environment for Controlling Robot Mobility 00:04:08
   • Reinforcement Learning Basics 00:15:55
   • Keras DQNs 00:03:59
   • DQN to Control a Robot's Mobility 00:13:20
   • The CartPole System 00:09:20
   • Q-learning Solution 00:14:23
   • Deep Q-learning Solution 00:11:19
   • Lesson Summary 00:01:24
4. Chapter 4 : Reuters Newswire Topics Classifier in Keras
   • Lesson Overview 00:01:11
   • Natural Language Processing 00:15:28
   • Sentiment Analysis 00:06:55
   • Natural Language Toolkit 00:04:05
   • Corpora 00:06:36
   • Word and Sentence Tokenize 00:10:29
   • Stemming 00:07:58
   • Implementing a DNN to Label Sentences 00:13:07
   • Data Preparation 00:15:04
   • Lesson Summary 00:01:57
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