Python Data Science Essentials: A practitioner's guide covering essential data science principles, tools, and techniques, 3rd Edition - Softcover

Massaron, Luca; Boschetti, Alberto

Softcover

ISBN 10: 178953786X ISBN 13: 9781789537864

Publisher: Packt Publishing, 2018

Synopsis

Gain useful insights from your data using popular data science tools

Key Features

• A one-stop 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 up-to-date insight into the core of Python, including the latest versions of the Jupyter Notebook, NumPy, pandas, and scikit-learn.

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 scikit-learn 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 real-world 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.

Table of Contents

1. First Steps
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. Appendix A: Strengthen Your Python Foundations

About this title

About the Author

Having joined Kaggle over 10 years ago, Luca Massaron is a Kaggle Grandmaster in discussions and a Kaggle Master in competitions and notebooks. In Kaggle competitions he reached no. 7 in the worldwide rankings. On the professional side, Luca is a data scientist with more than a decade of experience in transforming data into smarter artifacts, solving real-world problems, and generating value for businesses and stakeholders. He is a Google Developer Expert(GDE) in machine learning and the author of best-selling books on AI, machine learning, and algorithms.

Edition details

• Publisher: Packt Publishing
• Publication date: 2018
• Language: English
• ISBN 10: 178953786X
• ISBN 13: 9781789537864
• Binding: Paperback
• Edition number: 3
• Number of pages: 472