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Mastering Python for Data Science

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by Samir Madhavan
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Mastering Python for Data Science by Samir Madhavan

About This Book

  • Master data science methods using Python and its libraries
  • Create data visualizations and mine for patterns
  • Advanced techniques for the four fundamentals of Data Science with Python - data mining, data analysis, data visualization, and machine learning

Who This Book Is For

If you are a Python developer who wants to master the world of data science, then this book is for you. Some knowledge of data science is assumed.

What You Will Learn

  • Manage data and perform linear algebra in Python
  • Derive inferences from the analysis by performing inferential statistics
  • Solve data science problems in Python
  • Create high-end visualizations using Python
  • Evaluate and apply the linear regression technique to estimate the relationships among variables
  • Build recommendation engines with the various collaborative filtering algorithms
  • Apply the ensemble methods to improve your predictions
  • Work with big data technologies to handle data at scale

In Detail

Data science is a relatively new knowledge domain which is used by various organizations to make data-driven decisions. The Python programming language, beyond having conquered the scientific community in the last decade, is now an indispensable tool for the data science practitioner and a must-know tool for every aspiring data scientist.

This comprehensive guide helps you move beyond the hype and transcend the theory by providing you with a hands-on, advanced study of data science. Beginning with the essentials of Python in data science, you will learn to manage data and perform linear algebra in Python. You will move on to deriving inferences from the analysis by performing inferential statistics and mining data to reveal hidden patterns and trends.

You will then use the matplotlib library to create high-end visualizations in Python and uncover the fundamentals of machine learning. Next, you will apply the linear regression technique and also learn to apply the logistic regression technique to your applications, before finally performing k-means clustering, along with an analysis of unstructured data with different text mining techniques and leveraging the power of Python in big data analytics.

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Ebook Details
Pages: 294
Size: 5.8 MB
Publisher: Packt Publishing
Date published:   2015
ISBN: 2370006799597 (DRM-EPUB)

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Copying:not allowed
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This product is listed in the following categories:

Nonfiction > Computers > Database Management > Database Mining
Nonfiction > Computers > Programming Languages > Python
Nonfiction > Computers > Data Visualization

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