Book description
Gain useful insights from your data using popular data science tools
Key Features
 A onestop guide to Python libraries such as pandas and NumPy
 Comprehensive coverage of data science operations such as data cleaning and data manipulation
 Choose scalable learning algorithms for your data science tasks
Book Description
Fully expanded and upgraded, the latest edition of Python Data Science Essentials will help you succeed in data science operations using the most common Python libraries. This book offers uptodate insight into the core of Python, including the latest versions of the Jupyter Notebook, NumPy, pandas, and scikitlearn.
The book covers detailed examples and large hybrid datasets to help you grasp essential statistical techniques for data collection, data munging and analysis, visualization, and reporting activities. You will also gain an understanding of advanced data science topics such as machine learning algorithms, distributed computing, tuning predictive models, and natural language processing. Furthermore, You'll also be introduced to deep learning and gradient boosting solutions such as XGBoost, LightGBM, and CatBoost.
By the end of the book, you will have gained a complete overview of the principal machine learning algorithms, graph analysis techniques, and all the visualization and deployment instruments that make it easier to present your results to an audience of both data science experts and business users
What you will learn
 Set up your data science toolbox on Windows, Mac, and Linux
 Use the core machine learning methods offered by the scikitlearn library
 Manipulate, fix, and explore data to solve data science problems
 Learn advanced explorative and manipulative techniques to solve data operations
 Optimize your machine learning models for optimized performance
 Explore and cluster graphs, taking advantage of interconnections and links in your data
Who this book is for
If you're a data science entrant, data analyst, or data engineer, this book will help you get ready to tackle realworld data science problems without wasting any time. Basic knowledge of probability/statistics and Python coding experience will assist you in understanding the concepts covered in this book.
Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files emailed directly to you.
Publisher resources
Table of contents
 Title Page
 Copyright and Credits
 Packt Upsell
 Contributors
 Preface

First Steps
 Introducing data science and Python
 Installing Python
 Introducing Jupyter
 Datasets and code used in this book
 Summary
 Data Munging
 The Data Pipeline
 Machine Learning
 Visualization, Insights, and Results
 Social Network Analysis
 Deep Learning Beyond the Basics
 Spark for Big Data
 Strengthen Your Python Foundations
 Other Books You May Enjoy
Product information
 Title: Python Data Science Essentials  Third Edition
 Author(s):
 Release date: September 2018
 Publisher(s): Packt Publishing
 ISBN: 9781789537864
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