Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
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
Mastering Predictive Analytics with scikit-learn and TensorFlow

You're reading from   Mastering Predictive Analytics with scikit-learn and TensorFlow Implement machine learning techniques to build advanced predictive models using Python

Arrow left icon
Product type Paperback
Published in Sep 2018
Publisher Packt
ISBN-13 9781789617740
Length 154 pages
Edition 1st Edition
Languages
Arrow right icon
Author (1):
Arrow left icon
Alvaro Fuentes Alvaro Fuentes
Author Profile Icon Alvaro Fuentes
Alvaro Fuentes
Arrow right icon
View More author details
Toc

Predictions with TensorFlow

We will perform the hello world example of deep learning. This example is used to check and ensure that a model is working as intended. For this, we will use the MNIST dataset.

Introduction to the MNIST dataset

MNIST stands for Mixed National Institute of Standards and Technology, which has produced a handwritten digits dataset. This is one of the most researched datasets in machine learning, and is used to classify handwritten digits. This dataset is helpful for predictive analytics because of its sheer size, allowing deep learning to work its magic efficiently. This dataset contains 60,000 training images and 10,000 testing images, formatted as 28 x 28 pixel monochrome images. The following screenshot...

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
Banner background image