Practical Data Science with Python: Learn tools and techniques from hands-on examples to extract insights from data

Practical Data Science with Python teaches you core data science concepts, with real-world and realistic examples, and strengthens your grip on the basic as well as advanced principles of data preparation and storage, statistics, probability theory, machine learning, and Python programming, helping you build a solid foundation to gain proficiency in data science.

The book starts with an overview of basic Python skills and then introduces foundational data science techniques, followed by a thorough explanation of the Python code needed to execute the techniques. You'll understand the code by working through the examples. The code has been broken down into small chunks (a few lines or a function at a time) to enable thorough discussion.

As you progress, you will learn how to perform data analysis while exploring the functionalities of key data science Python packages, including pandas, SciPy, and scikit-learn. Finally, the book covers ethics and privacy concerns in data science and suggests resources for improving data science skills, as well as ways to stay up to date on new data science developments.

By the end of the book, you should be able to comfortably use Python for basic data science projects and should have the skills to execute the data science process on any data source.

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Practical Data Science with Python: Learn tools and techniques from hands-on examples to extract insights from data

Practical Data Science with Python teaches you core data science concepts, with real-world and realistic examples, and strengthens your grip on the basic as well as advanced principles of data preparation and storage, statistics, probability theory, machine learning, and Python programming, helping you build a solid foundation to gain proficiency in data science.

The book starts with an overview of basic Python skills and then introduces foundational data science techniques, followed by a thorough explanation of the Python code needed to execute the techniques. You'll understand the code by working through the examples. The code has been broken down into small chunks (a few lines or a function at a time) to enable thorough discussion.

As you progress, you will learn how to perform data analysis while exploring the functionalities of key data science Python packages, including pandas, SciPy, and scikit-learn. Finally, the book covers ethics and privacy concerns in data science and suggests resources for improving data science skills, as well as ways to stay up to date on new data science developments.

By the end of the book, you should be able to comfortably use Python for basic data science projects and should have the skills to execute the data science process on any data source.

43.99 In Stock
Practical Data Science with Python: Learn tools and techniques from hands-on examples to extract insights from data

Practical Data Science with Python: Learn tools and techniques from hands-on examples to extract insights from data

by Nathan George
Practical Data Science with Python: Learn tools and techniques from hands-on examples to extract insights from data

Practical Data Science with Python: Learn tools and techniques from hands-on examples to extract insights from data

by Nathan George

eBook

$43.99 

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Overview

Practical Data Science with Python teaches you core data science concepts, with real-world and realistic examples, and strengthens your grip on the basic as well as advanced principles of data preparation and storage, statistics, probability theory, machine learning, and Python programming, helping you build a solid foundation to gain proficiency in data science.

The book starts with an overview of basic Python skills and then introduces foundational data science techniques, followed by a thorough explanation of the Python code needed to execute the techniques. You'll understand the code by working through the examples. The code has been broken down into small chunks (a few lines or a function at a time) to enable thorough discussion.

As you progress, you will learn how to perform data analysis while exploring the functionalities of key data science Python packages, including pandas, SciPy, and scikit-learn. Finally, the book covers ethics and privacy concerns in data science and suggests resources for improving data science skills, as well as ways to stay up to date on new data science developments.

By the end of the book, you should be able to comfortably use Python for basic data science projects and should have the skills to execute the data science process on any data source.


Product Details

ISBN-13: 9781801076654
Publisher: Packt Publishing
Publication date: 09/30/2021
Sold by: Barnes & Noble
Format: eBook
Pages: 620
File size: 13 MB
Note: This product may take a few minutes to download.

About the Author

Nathan George is a data scientist at Tink in Stockholm, Sweden, and taught data science as a professor at Regis University in Denver, CO for over 4 years. Nathan has created online courses on Pythonic data science and uses Python data science tools for electroencephalography (EEG) research with the OpenBCI headset and public EEG data. His education includes the Galvanize data science immersive, a PhD from UCSB in Chemical Engineering, and a BS in Chemical Engineering from the Colorado School of Mines.

Table of Contents

Table of Contents
  1. Introduction to Data Science
  2. Getting Started with Python
  3. SQL and Built-in File Handling Modules in Python
  4. Loading and Wrangling Data with Pandas and NumPy
  5. Exploratory Data Analysis and Visualization
  6. Data Wrangling Documents and Spreadsheets
  7. Web Scraping
  8. Probability, Distributions, and Sampling
  9. Statistical Testing for Data Science
  10. Preparing Data for Machine Learning: Feature Selection, Feature Engineering, and Dimensionality Reduction
  11. Machine Learning for Classification
  12. Evaluating Machine Learning Classification Models and Sampling for Classification
  13. Machine Learning with Regression
  14. (N.B. Please use the Look Inside option to see further chapters)

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