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Python Data Science Essentials

You're reading from   Python Data Science Essentials A practitioner's guide covering essential data science principles, tools, and techniques

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Product type Paperback
Published in Sep 2018
Publisher Packt
ISBN-13 9781789537864
Length 472 pages
Edition 3rd Edition
Languages
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Authors (2):
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Luca Massaron Luca Massaron
Author Profile Icon Luca Massaron
Luca Massaron
Alberto Boschetti Alberto Boschetti
Author Profile Icon Alberto Boschetti
Alberto Boschetti
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Toc

Table of Contents (11) Chapters Close

Preface 1. First Steps FREE CHAPTER 2. Data Munging 3. The Data Pipeline 4. Machine Learning 5. Visualization, Insights, and Results 6. Social Network Analysis 7. Deep Learning Beyond the Basics 8. Spark for Big Data 9. Strengthen Your Python Foundations 10. Other Books You May Enjoy

Approaching deep learning

Deep learning is an extension of the classical machine-learning approach using neural networks: instead of building networks of a few layers (so-called shallow networks), we can stack hundreds of layers to create an elaborate, but more powerful, learner. Deep learning is one of the most popular methods of artificial intelligence (AI) nowadays since it's very effective and helps to solve many problems in pattern recognition, such as object or sequence identification, which seemed unbreakable using standard machine learning tools.

The idea of neural networks came from the human central nervous system, where multiple nodes (or neurons) that are able to process simple information are connected together to create a network capable of processing complex information. In fact, neural networks are so named because they can learn the weights of the model...

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