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Practical Statistics for Data Scientists: 50 Essential Concepts

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Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not.

Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.

With this book, you’ll learn:

  • Why exploratory data analysis is a key preliminary step in data science
  • How random sampling can reduce bias and yield a higher quality dataset, even with big data
  • How the principles of experimental design yield definitive answers to questions
  • How to use regression to estimate outcomes and detect anomalies
  • Key classification techniques for predicting which categories a record belongs to
  • Statistical machine learning methods that “learn” from data
  • Unsupervised learning methods for extracting meaning from unlabeled data
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Practical Data Wrangling: Expert techniques for transforming your raw data into a valuable source for analytics
Practical Data Wrangling: Expert techniques for transforming your raw data into a valuable source for analytics

Key Features

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  • Work with different types of datasets, and reshape the layout of your data to make it easier for analysis
  • Get simple examples and real-life data...
Deep Learning Cookbook: Practical Recipes to Get Started Quickly
Deep Learning Cookbook: Practical Recipes to Get Started Quickly

Deep learning doesn’t have to be intimidating. Until recently, this machine-learning method required years of study, but with frameworks such as Keras and Tensorflow, software engineers without a background in machine learning can quickly enter the field. With the recipes in this cookbook, you’ll learn how to solve...

Begin to Code with Python
Begin to Code with Python

Become a Python programmer–and have fun doing it!

Start writing software that solves real problems, even if you have absolutely no programming experience! This friendly, easy, full-color book puts you in total control of your own learning, empowering you to build...


Python 3 Text Processing with NLTK 3 Cookbook
Python 3 Text Processing with NLTK 3 Cookbook

Over 80 practical recipes on natural language processing techniques using Python's NLTK 3.0

About This Book

  • Break text down into its component parts for spelling correction, feature extraction, and phrase transformation
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Practical LPIC-1 Linux Certification Study Guide
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This book is your complete guide to studying for the Linux Professional Institute's Server Professional (LPIC-1) certification. Every concept, principle, process, and resource that might make an appearance on the exam is fully represented. You will understand every concept by rolling up your sleeves, opening up a terminal,...
Git : Best Practices Guide
Git : Best Practices Guide

Master the best practices of Git with the help of real-time scenarios to maximize team efficiency and workflow

About This Book

  • Work with a versioning tool for continuous integration using Git
  • Learn how to make the best use of Git's features
  • Comprehensible guidelines...
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