Beginning R: An Introduction to Statistical Programming
Beginning R, Second Edition is a hands-on book showing how to use the R language, write and save R scripts, read in data files, and write custom statistical functions as well as use built in functions. This book shows the use of R in specific cases such as one-way ANOVA analysis, linear and logistic regression, data visualization,...
Mastering Machine Learning With scikit-learn
Apply effective learning algorithms to real-world problems using scikit-learn
About This Book
Design and troubleshoot machine learning systems for common tasks including regression, classification, and clustering
Acquaint yourself with popular machine learning algorithms, including...
Categorical Data Analysis Using SAS, Third Edition
Statisticians and researchers will find Categorical Data Analysis Using SAS, Third Edition, by Maura Stokes, Charles Davis, and Gary Koch, to be a useful discussion of categorical data analysis techniques as well as an invaluable aid in applying these methods with SAS. Practical examples from a broad range of applications illustrate...
Practical Data Science with R
Practical Data Science with R lives up to its name. It explains basic principles without the theoretical mumbo-jumbo and jumps right to the real use cases you'll face as you collect, curate, and analyze the data crucial to the success of your business. You'll apply the R programming language...
Practical Statistics for Data Scientists: 50 Essential Concepts
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...
Python for Finance: Analyze Big Financial Data
The financial industry has adopted Python at a tremendous rate recently, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. This hands-on guide helps both developers and quantitative analysts get started with Python, and guides you through the most important aspects...
Machine Learning with R - Second Edition
Harness the power of R for statistical computing and data science
Explore, forecast, and classify data with R
Use R to apply common machine learning algorithms to real-world scenarios
Machine learning, at its core, is concerned...
Doing Data Science: Straight Talk from the Frontline
Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to...
The Book of R: A First Course in Programming and Statistics
The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical...
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