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

This lesson concludes our journey into creating a deep learning model and deploying it as a web application. Our very last steps included deploying a model that predicts Bitcoin prices built using Keras and the TensorFlow engine. We finished our work by packaging the application as a Docker container and deploying it so that others can consume the predictions of our model, as well as other applications, via its API.

Aside from that work, you have also learned that there is much that can be improved. Our Bitcoin model is only an example of what a model can do (particularly LSTMs). The challenge now is twofold: how can you make that model perform better as time passes? And what features can you add to your web application to make your model more accessible? With the concepts you've learned in this book, you will be able to develop models and keep enhancing them to make accurate predictions.