October 2018
Intermediate to advanced
472 pages
10h 57m
English
Content preview from Python Deep Learning Projects
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Exploring the MNIST dataset
Before we jump into building our awesome neural network, let's first have a look at the famous MNIST dataset. So let's visualize the MNIST dataset in this section.
Words of wisdom: You must know your data and how it has been preprocessed, in order to know why the models you build perform the way they do. This section reviews the significant work that has been done in preparation on the dataset, to make our current job of building the MLP easier. Always remember: data science begins with DATA!
Let's start therefore by downloading the data, using the following commands:
from tensorflow.examples.tutorials.mnist import input_datamnist = input_data.read_data_sets("/tmp/data/", one_hot=True)
If we examine the mnist ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.