Python Data Science Essentials: Become an efficient data science practitioner by thoroughly understanding the key concepts of Python

Massaron, Luca,Boschetti, Alberto

ISBN 10: 1785280422 / ISBN 13: 9781785280429

Published by Packt Publishing, 2015

About this Item

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Bibliographic Details

Title: Python Data Science Essentials: Become an ...

Publisher: Packt Publishing

Publication Date: 2015

Binding: Paperback

Condition: Good

About this title

Synopsis:

Key Features

• Quickly get familiar with data science using Python
• Save time - and effort - with all the essential tools explained
• Create effective data science projects and avoid common pitfalls with the help of examples and hints dictated by experience

Book Description

The book starts by introducing you to setting up your essential data science toolbox. Then it will guide you across all the data munging and preprocessing phases. This will be done in a manner that explains all the core data science activities related to loading data, transforming and fixing it for analysis, as well as exploring and processing it. Finally, it will complete the overview by presenting you with the main machine learning algorithms, the graph analysis technicalities, and all the visualization instruments that can make your life easier in presenting your results.

In this walkthrough, structured as a data science project, you will always be accompanied by clear code and simplified examples to help you understand the underlying mechanics and real-world datasets.

What you will learn

• Set up your data science toolbox using a Python scientific environment on Windows, Mac, and Linux
• Get data ready for your data science project
• Manipulate, fix, and explore data in order to solve data science problems
• Set up an experimental pipeline to test your data science hypothesis
• Choose the most effective and scalable learning algorithm for your data science tasks
• Optimize your machine learning models to get the best performance
• Explore and cluster graphs, taking advantage of interconnections and links in your data

Table of Contents

1. First Steps
2. Data Munging
3. The Data Science Pipeline
4. Machine Learning
5. Social Network Analysis
6. Visualization

About the Author:

Alberto Boschetti

Alberto Boschetti is a data scientist with expertise in signal processing and statistics. He holds a PhD in telecommunication engineering and currently lives and works in London. In his work projects, he faces challenges involving natural language processing (NLP), machine learning, and probabilistic graph models everyday. He is very passionate about his job and he always tries to stay updated on the latest developments in data science technologies by attending meetups, conferences, and other events.