Book Image

Deep Learning with TensorFlow - Second Edition

By : Giancarlo Zaccone, Md. Rezaul Karim
Book Image

Deep Learning with TensorFlow - Second Edition

By: Giancarlo Zaccone, Md. Rezaul Karim

Overview of this book

Deep learning is a branch of machine learning algorithms based on learning multiple levels of abstraction. Neural networks, which are at the core of deep learning, are being used in predictive analytics, computer vision, natural language processing, time series forecasting, and to perform a myriad of other complex tasks. This book is conceived for developers, data analysts, machine learning practitioners and deep learning enthusiasts who want to build powerful, robust, and accurate predictive models with the power of TensorFlow, combined with other open source Python libraries. Throughout the book, you’ll learn how to develop deep learning applications for machine learning systems using Feedforward Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Autoencoders, and Factorization Machines. Discover how to attain deep learning programming on GPU in a distributed way. You'll come away with an in-depth knowledge of machine learning techniques and the skills to apply them to real-world projects.
Table of Contents (15 chapters)
Deep Learning with TensorFlow - Second Edition
Contributors
Preface
Other Books You May Enjoy
Index

Linear regression and beyond


In this section, we will take a closer look at the main concepts of TensorFlow and TensorBoard and try to do some basic operations to get you started. The model we want to implement simulates linear regression.

In statistics and ML, linear regression is a technique that's frequently used to measure the relationship between variables. This is a quite simple but effective algorithm that can be used in predictive modeling as well.

Linear regression models the relationship between a dependent variable, , an interdependent variable,

, and a random term, b. This can be seen as follows:

A typical linear regression problem using TensorFlow has the following workflow, which updates the parameters to minimize the given cost (see in the following figure) function:

Figure 9: A learning algorithm using linear regression in TensorFlow

Now, let's try to follow the preceding figure and reproduce it for the linear regression by conceptualizing the preceding equation. For this, we...