Home | Amazing | Today | Tags | Publishers | Years | Account | Search 
Loading
Practical Statistics for Data Scientists: 50 Essential Concepts

Buy

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
(HTML tags aren't allowed.)

The Data Science Design Manual (Texts in Computer Science)
The Data Science Design Manual (Texts in Computer Science)

This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data.

The...

Practical Data Science Cookbook - Second Edition
Practical Data Science Cookbook - Second Edition

Over 85 recipes to help you complete real-world data science projects in R and Python

About This Book

  • Tackle every step in the data science pipeline and use it to acquire, clean, analyze, and visualize your data
  • Get beyond the theory and implement real-world projects in data science using...
Practical Data Science Cookbook - Real-World Data Science Projects to Help You Get Your Hands On Your Data
Practical Data Science Cookbook - Real-World Data Science Projects to Help You Get Your Hands On Your Data

Key Features

  • Learn how to tackle every step in the data science pipeline and use it to acquire, clean, analyze, and visualize data
  • Get beyond the theory with real-world projects
  • Expand your numerical programming skills through step-by-step code examples and learn more about the robust...

Mastering Java Machine Learning: Mastering and implementing advanced techniques in machine learning
Mastering Java Machine Learning: Mastering and implementing advanced techniques in machine learning

Become an advanced practitioner with this progressive set of master classes on application-oriented machine learning

About This Book

  • Comprehensive coverage of key topics in machine learning with an emphasis on both the theoretical and practical aspects
  • More than 15 open source Java tools...
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...
Microservices Deployment Cookbook
Microservices Deployment Cookbook

Key Features

  • Adopt microservices-based architecture and deploy it at scale
  • Build your complete microservice architecture using different recipes for different solutions
  • Identify specific tools for specific scenarios and deliver immediate business results, correlate use cases, and adopt them...
©2017 LearnIT (support@pdfchm.net) - Privacy Policy