Home | Amazing | Today | Tags | Publishers | Years | Account | Search 
Loading
Practical Data Science Cookbook - Second Edition

Buy

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 R and Python
  • Easy-to-follow recipes will help you understand and implement the numerical computing concepts

Who This Book Is For

If you are an aspiring data scientist who wants to learn data science and numerical programming concepts through hands-on, real-world project examples, this is the book for you. Whether you are brand new to data science or you are a seasoned expert, you will benefit from learning about the structure of real-world data science projects and the programming examples in R and Python.

What You Will Learn

  • Learn and understand the installation procedure and environment required for R and Python on various platforms
  • Prepare data for analysis by implement various data science concepts such as acquisition, cleaning and munging through R and Python
  • Build a predictive model and an exploratory model
  • Analyze the results of your model and create reports on the acquired data
  • Build various tree-based methods and Build random forest

In Detail

As increasing amounts of data are generated each year, the need to analyze and create value out of it is more important than ever. Companies that know what to do with their data and how to do it well will have a competitive advantage over companies that don't. Because of this, there will be an increasing demand for people that possess both the analytical and technical abilities to extract valuable insights from data and create valuable solutions that put those insights to use.

Starting with the basics, this book covers how to set up your numerical programming environment, introduces you to the data science pipeline, and guides you through several data projects in a step-by-step format. By sequentially working through the steps in each chapter, you will quickly familiarize yourself with the process and learn how to apply it to a variety of situations with examples using the two most popular programming languages for data analysis-R and Python.

Style and approach

This step-by-step guide to data science is full of hands-on examples of real-world data science tasks. Each recipe focuses on a particular task involved in the data science pipeline, ranging from readying the dataset to analytics and visualization

(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 - 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...

C++17 STL Cookbook
C++17 STL Cookbook

Key Features

  • Learn the latest features of C++ and how to write better code by using the Standard Library (STL). Reduce the development time for your applications.
  • Understand the scope and power of STL features to deal with real-world problems.
  • Compose your own algorithms without forfeiting...
The Measure of All Minds: Evaluating Natural and Artificial Intelligence
The Measure of All Minds: Evaluating Natural and Artificial Intelligence

Are psychometric tests valid for a new reality of artificial intelligence systems, technology-enhanced humans, and hybrids yet to come? Are the Turing Test, the ubiquitous CAPTCHAs, and the various animal cognition tests the best alternatives? In this fascinating and provocative book, José Hernández-Orallo formulates major...

Learning Python Application Development
Learning Python Application Development

Key Features

  • Get to grips with Python techniques that address commonly encountered problems in general application development.
  • Develop, package, and deploy efficient applications in a fun way.
  • All-practical coverage of the major areas of application development, including best practices,...
©2017 LearnIT (support@pdfchm.net) - Privacy Policy