Book Image

Hands-On Deep Learning with TensorFlow

By : Dan Van Boxel
Book Image

Hands-On Deep Learning with TensorFlow

By: Dan Van Boxel

Overview of this book

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.
Table of Contents (12 chapters)

TensorFlow learn


Just as Scikit-Learn is a convenient interface to traditional machine learning algorithms, tf.contrib.learn (https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/learn/python/learn), formerly known as skflow, it is a simplified interface to build and train DNNs. Now it comes free with every installation of TensorFlow!

Even if you're not a fan of the syntax, it's worth looking at TensorFlow Learn as the high-level API to TensorFlow. This is because it's currently the only officially supported one. But, you should know that there are many alternative high-level APIs that may have more intuitive interfaces. If interested, refer to Keras (https://keras.io/), tf.slim (included with TF), to learn more about TensorFlow-Slim refer to https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/slim or TFLearn (http://tflearn.org/).

Setup

To get started with TensorFlow Learn, you only need to import it. We'll also import the estimators function, which will...