Book description
Leverage the power of Tensorflow to design deep learning systems for a variety of real-world scenarios
About This Book
- Build efficient deep learning pipelines using the popular Tensorflow framework
- Train neural networks such as ConvNets, generative models, and LSTMs
- Includes projects related to Computer Vision, stock prediction, chatbots and more
Who This Book Is For
This book is for data scientists, machine learning developers as well as deep learning practitioners, who want to build interesting deep learning projects that leverage the power of Tensorflow. Some understanding of machine learning and deep learning, and familiarity with the TensorFlow framework is all you need to get started with this book.
What You Will Learn
- Set up the TensorFlow environment for deep learning
- Construct your own ConvNets for effective image processing
- Use LSTMs for image caption generation
- Forecast stock prediction accurately with an LSTM architecture
- Learn what semantic matching is by detecting duplicate Quora questions
- Set up an AWS instance with TensorFlow to train GANs
- Train and set up a chatbot to understand and interpret human input
- Build an AI capable of playing a video game by itself ?and win it!
In Detail
TensorFlow is one of the most popular frameworks used for machine learning and, more recently, deep learning. It provides a fast and efficient framework for training different kinds of deep learning models, with very high accuracy. This book is your guide to master deep learning with TensorFlow with the help of 10 real-world projects.
TensorFlow Deep Learning Projects starts with setting up the right TensorFlow environment for deep learning. Learn to train different types of deep learning models using TensorFlow, including Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, and Generative Adversarial Networks. While doing so, you will build end-to-end deep learning solutions to tackle different real-world problems in image processing, recommendation systems, stock prediction, and building chatbots, to name a few. You will also develop systems that perform machine translation, and use reinforcement learning techniques to play games.
By the end of this book, you will have mastered all the concepts of deep learning and their implementation with TensorFlow, and will be able to build and train your own deep learning models with TensorFlow confidently.
Style and approach
This book contains 10 unique, end-to-end projects covering all aspects of deep learning and their implementations with TensorFlow. Each project will equip you with a unique skillset in training efficient deep learning models, and empower you to implement your own projects more confidently
Table of contents
- Title Page
- Copyright and Credits
- Packt Upsell
- Contributors
- Preface
- Recognizing traffic signs using Convnets
- Annotating Images with Object Detection API
- Caption Generation for Images
- Building GANs for Conditional Image Creation
- Stock Price Prediction with LSTM
- Create and Train Machine Translation Systems
- Train and Set up a Chatbot, Able to Discuss Like a Human
-
Detecting Duplicate Quora Questions
- Presenting the dataset
- Starting with basic feature engineering
- Creating fuzzy features
- Resorting to TF-IDF and SVD features
- Mapping with Word2vec embeddings
- Testing machine learning models
- Building a TensorFlow model
- Processing before deep neural networks
- Deep neural networks building blocks
- Designing the learning architecture
- Summary
- Building a TensorFlow Recommender System
- Video Games by Reinforcement Learning
- Other Books You May Enjoy
Product information
- Title: TensorFlow Deep Learning Projects
- Author(s):
- Release date: March 2018
- Publisher(s): Packt Publishing
- ISBN: 9781788398060
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