Hands-On Deep Learning with TensorFlow

English | 2017 | ISBN: 978-1787282773 | 174 Pages | EPUB, AZW3, PDF (conv) | 16 MB

This book is your guide to exploring the possibilities in the field of deep learning, making use of Google’s TensorFlow. You will learn about convolutional neural networks, and logistic regression while training models for deep learning to gain key insights into your data.
Dan Van Boxel’s Deep Learning with TensorFlow is based on Dan’s best-selling TensorFlow video course. With deep learning going mainstream, making sense of data and getting accurate results using deep networks is possible. Dan Van Boxel will be your guide to exploring the possibilities with deep learning; he will enable you to understand data like never before. With the efficiency and simplicity of TensorFlow, you will be able to process your data and gain insights that will change how you look at data.
With Dan’s guidance, you will dig deeper into the hidden layers of abstraction using raw data. Dan then shows you various complex algorithms for deep learning and various examples that use these deep neural networks. You will also learn how to train your machine to craft new features to make sense of deeper layers of data.
In this book, Dan shares his knowledge across topics such as logistic regression, convolutional neural networks, recurrent neural networks, training deep networks, and high level interfaces. With the help of novel practical examples, you will become an ace at advanced multilayer networks, image recognition, and beyond.
What You Will Learn

• Set up your computing environment and install TensorFlow
• Build simple TensorFlow graphs for everyday computations
• Apply logistic regression for classification with TensorFlow
• Design and train a multilayer neural network with TensorFlow
• Intuitively understand convolutional neural networks for image recognition
• Bootstrap a neural network from simple to more accurate models
• See how to use TensorFlow with other types of networks
• Program networks with SciKit-Flow, a high-level interface to TensorFlow