The Applied TensorFlow and Keras Workshop: Develop your practical skills by working through a real-world project and build your own Bitcoin price prediction tracker

Cut through the noise and get real results with this workshop for beginners. Use a project-based approach to exploring machine learning with TensorFlow and Keras.

Key Features

• Understand the nuances of setting up a deep learning programming environment
• Gain insights into the common components of a neural network and its essential operations
• Get to grips with deploying a machine learning model as an interactive web application with Flask

Book Description

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.

What you will learn

• Familiarize yourself with the components of a neural network
• Understand the different types of problems that can be solved using neural networks
• Explore different ways to select the right architecture for your model
• Make predictions with a trained model using TensorBoard
• Discover the components of Keras and ways to leverage its features in your model
• Explore how you can deal with new data by learning ways to retrain your model

Who this book is for

If you are a data scientist or a machine learning and deep learning enthusiast, who is looking to design, train, and deploy TensorFlow and Keras models into real-world applications, then this workshop is for you. Knowledge of computer science and machine learning concepts and experience in analyzing data will help you to understand the topics explained in this book with ease.

Table of Contents

1. Introduction to Neural Networks and Deep Learning
2. Real-World Deep Learning: Predicting the Price of Bitcoin
3. Real-World Deep Learning: Evaluating the Bitcoin Model
4. Productization

Harveen Singh Chadha is an experienced researcher in deep learning and is currently working as a self-driving car engineer. He is focused on creating an advanced driver assistance systems (ADAS) platform. His passion is to help people who want to enter the data science universe. He is the author of the video course Hands-On Neural Network Programming with TensorFlow.

Luis Capelo is a Harvard-trained analyst and a programmer, who specializes in designing and developing data science products. He is based in New York City, America. Luis is the head of the Data Products team at Forbes, where they investigate new techniques for optimizing article performance and create clever bots that help them distribute their content. He worked for the United Nations as part of the Humanitarian Data Exchange team (founders of the Center for Humanitarian Data). Later on, he led a team of scientists at the Flowminder Foundation, developing models for assisting the humanitarian community. Luis is a native of Havana, Cuba, and the founder and owner of a small consultancy firm dedicated to supporting the nascent Cuban private sector.