Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Applied Deep Learning with Python

You're reading from   Applied Deep Learning with Python Use scikit-learn, TensorFlow, and Keras to create intelligent systems and machine learning solutions

Arrow left icon
Product type Paperback
Published in Aug 2018
Publisher
ISBN-13 9781789804744
Length 334 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Authors (2):
Arrow left icon
Alex Galea Alex Galea
Author Profile Icon Alex Galea
Alex Galea
Luis Capelo Luis Capelo
Author Profile Icon Luis Capelo
Luis Capelo
Arrow right icon
View More author details
Toc

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 experiences on how to train a highly performant neural network and also 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 during Chapter 5, Model Architecture. In Chapter 6, Model Evaluation and Optimization, we will evaluate and improve that model and, finally, in Chapter 7, Productization, we will create a program that serves the prediction of that system via an HTTP API.

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime