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.
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
* 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