Book Image

The Applied TensorFlow and Keras Workshop

By : Harveen Singh Chadha, Luis Capelo
Book Image

The Applied TensorFlow and Keras Workshop

By: Harveen Singh Chadha, Luis Capelo

Overview of this book

Machine learning gives computers the ability to learn like humans. It is becoming increasingly transformational to businesses in many forms, and a key skill to learn to prepare for the future digital economy. As a beginner, you’ll unlock a world of opportunities by learning the techniques you need to contribute to the domains of machine learning, deep learning, and modern data analysis using the latest cutting-edge tools. The Applied TensorFlow and Keras Workshop begins by showing you how neural networks work. After you’ve understood the basics, you will train a few networks by altering their hyperparameters. To build on your skills, you’ll learn how to select the most appropriate model to solve the problem in hand. While tackling advanced concepts, you’ll discover how to assemble a deep learning system by bringing together all the essential elements necessary for building a basic deep learning system - data, model, and prediction. Finally, you’ll explore ways to evaluate the performance of your model, and improve it using techniques such as model evaluation and hyperparameter optimization. By the end of this book, you'll have learned how to build a Bitcoin app that predicts future prices, and be able to build your own models for other projects.
Table of Contents (6 chapters)

Summary

In this chapter, we explored a TensorFlow-trained neural network using TensorBoard and trained our own modified version of that network with different epochs and learning rates. This gave you hands-on experience of how to train a highly performant neural network and allowed you to explore some of its limitations.

Do you think we can achieve similar accuracy with real Bitcoin data? We will attempt to predict future Bitcoin prices using a common neural network algorithm in Chapter 2, Real-World Deep Learning: Predicting the Price of Bitcoin. In Chapter 3, Real-World Deep Learning: Evaluating the Bitcoin Model, we will evaluate and improve that model, and finally, in Chapter 4, Productization, we will create a program that serves the prediction of that system via an HTTP API.