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Python for Data Analysis: Master Deep Learning with Python Language and Become Great at Programming Python for Beginners with Hands-on Project (Data Science)
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Python
for Data Analysis

Master Deep Learning with Python Language and Become Great at Programming Python for Beginners with Hands-on Project (Data Science)

Jason Scratch

The content contained within this book may not be reproduced, duplicated or transmitted without direct written permission from the author or the publisher.

Under no circumstances will any blame or legal responsibility be held against the publisher, or author, for any damages, reparation, or monetary loss due to the information contained within this book. Either directly or indirectly.

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Please note the information contained within this document is for educational and entertainment purposes only. All effort has been executed to present accurate, up to date, and reliable, complete information. No warranties of any kind are declared or implied. Readers acknowledge that the author is not engaging in the rendering of legal, financial, medical or professional advice. The content within this book has been derived from various sources. Please consult a licensed professional before attempting any techniques outlined in this book.

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Table of Contents

Introduction

C ongratulations on purchasing Python for Data Analysis and thank you for doing so.

The following chapters will discuss everything that we need to know when it comes to deep learning and a good data analysis. Many companies are shifting the way they do things. Collecting data has become the norm, and now they have to learn what is inside all of that data, and what insights they can learn in the process. And this is exactly what a data analysis can help them to do. With a bit of the Python language, an understanding of deep learning, and some of the best deep learning libraries available we can create our own models and put that data to work.

To start this guidebook, we are going to take a look at some of the basics of deep learning and what data analysis is all about. There are a lot of buzz words out there when it comes to machine learning and artificial intelligence, and understanding how these two topics can fit into the mix is so important for ensuring that we will get things done.

From there, we will move a bit into Python and how it fits into this process. We will start this with some information on the best libraries form Python that help with deep learning before moving on to how we can work with some of the different types of neural networks you can create. This section is also a great one to explore to learn more about some of the Python deep learning libraries you can use including TensorFlow, Keras, and PyTorch and how these can help us create some of the models that we want within the field of deep learning and data analysis.

To end this guidebook, we will take a look at machine learning and how this process can fit in with the other topics we have discussed, especially when we look at deep learning. And then we end with a discussion on how deep learning can help businesses with their own predictive analysis. This makes it easier for companies to make data-based business decisions to help them get ahead on the market.

A data analysis is an important part of any business, especially those who have spent a lot of time collecting big data. But doing this in the right manner can be critical to ensure we get accurate insights and predictions. When you are ready to learn more

There are plenty of books on this subject on the market, thanks again for choosing this one! Every effort was made to ensure it is full of as much useful information as possible, please enjoy!

Chapter 1:

What Is Deep Learning?

T he world of data science and the various terms and processes that go with it has really taken off steam. Many companies have started to realize that they can use this information and the fact that computers and systems are able to train themselves, for their own advantage, and they are excited to learn more about how to make this happen.

No matter what industry you are in, processes like data analysis, machine learning, artificial intelligence, and deep learning can come into play and provide you with some great results in the process. But with this in mind, we are going to spend some time focusing on deep learning and what it is able to do for your business.

Deep learning is a process that can carry out what we need with the world of machine learning, often using an artificial neural net that is composed of a lot of levels arranged in a type of hierarchy to make things easier. The network is going to learn something simple when you enter into the first level, and then it will work to send that information, and everything that it has learned in that part, over to the next level .

From here, the next level is able to take some of this simple information and will try to combine it together with something that is seen as a bit more complex, before passing all of that over to the third level. This is a process that will just continue from one level to the next, with each level building something that is more complex from any input that it received with the previous level.

This is an interesting process that shows us exactly how deep learning is meant to work, and why it is so valuable. It is basically a process where the computer is able to teach itself how to learn, based on a simple program that a data scientist is able to add to the system. It is that easy! We will talk about some of the best libraries and the best algorithms from machine learning and deep learning to make this happen, but having a good understanding of how it all works can really make a difference in how you are able to use it.

What Is Deep Learning

The first topic that we need to dive into here is what deep learning is all about. Deep learning is considered a function that comes with artificial intelligence, one that is able to imitate, as closely as possible, some of the workings we see in the human brain when it comes to creating patterns and processing complex data to use with decision making. Basically, we can use the parts of deep learning to help us take our machine or our system and teach it how to think through things the same way that a human can, although at a faster and more efficient rate.

Deep learning is going to be considered a subset of machine learning, which is also a subset of artificial intelligence. It also has a network that is capable of learning a lot from data that is unsupervised, along with data that is unlabeled or unstructured. There are other names for this kind of learning as well including deep neural network and deep neural learning.

So, to get a better idea of how this is going to benefit us, we first need to take a look at how we can work with deep learning. The process of deep learning has really evolved a lot in the past few years, going hand in hand with a lot of the things we have seen in the digital era. This time period has really brought about so much data, data that comes in so many forms. In particular, this data is known as big data, and we will be able to draw it out of a lot of different areas such as e-commerce platforms, search engines, social media, and more.

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