Hands-On Deep Learning with TensorFlow

Key Features

• Explore various possibilities with deep learning and gain amazing insights from data using Google's brainchild-- TensorFlow
• Want to learn what more can be done with deep learning? Explore various neural networks with the help of this comprehensive guide
• Rich in concepts, advanced guide on deep learning that will give you background to innovate in your environment

Book Description

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

About the Author

Dan Van Boxel is a data scientist and machine learning engineer with over 10 years of experience. He is most well-known for Dan Does Data, a YouTube livestream demonstrating the power and pitfalls of neural networks. He has developed and applied novel statistical models of machine learning to topics such as accounting for truck traffic on highways, travel time outlier detection, and other areas. Dan has also published research articles and presented findings at the Transportation Research Board and other academic journals.

Table of Contents

1. Getting Started
2. Deep Neural Networks
3. Convolutional Neural Networks
4. Recurrent Neural Networks
5. Wrapping Up

Dan Van Boxel

Dan Van Boxel is a data scientist and machine learning engineer with over 10 years of experience. He is most well-known for Dan Does Data, a YouTube livestream demonstrating the power and pitfalls of neural networks. He has developed and applied novel statistical models of machine learning to topics such as accounting for truck traffic on highways, travel time outlier detection, and other areas. Dan has also published research articles and presented findings at the Transportation Research Board and other academic journals.