Statistical Foundations of Data Science (Chapman & Hall/CRC Data Science Series) - Image 1

£97.00

CRC Press Statistical Foundations of Data Science (Chapman & Hall/CRC Data Science Series)

Name: Statistical Foundations of Data Science (Chapman & Hall/CRC Data Science Series)
Brand: CRC Press
Price: 97.0 GBP
Availability: InStock

Reference

This is the usual price. Wait for it to drop, or tell us your number.

£97 today · usual range £0–£0 · best ever £84

NEW HERE?

Amazon shows you one price. We show you all of them.

Tosheroon watches Amazon prices so you don't have to. Every product on Amazon has a price history — we make it visible. Set the price you'd actually pay, and we'll email you the second it gets there. No app, no account, one email.

WHAT'S ON THIS PAGE

↓ Price chart
when this has been cheap or pricey

↓ Forecast
where the price is heading next

↓ Statistics
all-time high & low, recent range

↑ Price alert
name your number, we'll email you

Price History & Forecast

Grey patches = out of stock. Cheaper = lower on the chart. Hover for exact prices.

Last 579 days • 579 data points (No recent data available)

Historical

Generating forecast...

Price Distribution

Price distribution over 579 days • 5 price ranges

Days at Price

Current Price

Price Analysis

Most common range: £92-96 (281 days, 48.5%)

Price range: £84 - £104

Price levels: 5 price ranges over 579 days

Description

Statistical Foundations of Data Science gives a thorough introduction to commonly used statistical models, contemporary statistical machine learning techniques and algorithms, along with their mathematical insights and statistical theories. It aims to serve as a graduate-level textbook and a research monograph on high-dimensional statistics, sparsity and covariance learning, machine learning, and statistical inference. It includes ample exercises that involve both theoretical studies as well as empirical applications. The book begins with an introduction to the stylized features of big data and their impacts on statistical analysis. It then introduces multiple linear regression and expands the techniques of model building via nonparametric regression and kernel tricks. It provides a comprehensive account on sparsity explorations and model selections for multiple regression, generalized linear models, quantile regression, robust regression, hazards regression, among others. High-dimensional inference is also thoroughly addressed and so is feature screening. The book also provides a comprehensive account on high-dimensional covariance estimation, learning latent factors and hidden structures, as well as their applications to statistical estimation, inference, prediction and machine learning problems. It also introduces thoroughly statistical machine learning theory and methods for classification, clustering, and prediction. These include CART, random forests, boosting, support vector machines, clustering algorithms, sparse PCA, and deep learning.

Key Features

New Store Stock

Product Specifications

Brand: CRC Press
Format: hardcover
ASIN: 1466510846
Category: Books > Subjects > Reference
Domain: Amazon UK
Release Date: 17 August 2020
Listed Since: 02 August 2012

Barcode

No barcode data available

CRC Press Statistical Foundations of Data Science (Chapman & Hall/CRC Data Science Series)

This is the usual price. Wait for it to drop, or tell us your number.

Price History & Forecast

Price Distribution

Price Analysis

Description

Key Features

Product Specifications

Barcode

Similar Products You Might Like

Perspectives on Big Data Analysis: Methodologies and Applications: International Workshop on Perspectives on High-Dimension Data Anlaysis II, May ... Quebec, Canada (Contemporary Mathematics)

Hands-On Machine Learning with R (Chapman & Hall/CRC The R Series)

Statistical Learning and Data Science (Chapman & Hall/CRC Computer Science & Data Analysis)

Data Science in Theory and Practice: Techniques for Big Data Analytics and Complex Data Sets

An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)

The Oxford Handbook of Functional Data Analysis

Data Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving (Chapman & Hall/CRC: The R Series)

No Bullshit Math for Data Science: Your Comprehensive, Short and Sharp Guide to the Mathematics of Data Science

Statistical Learning and Data Science (Computer Science and Data Analysis)

A User's Guide to Business Analytics

Data Science Using Python and R (Wiley Series on Methods and Applications in Data Mining)

Data Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving (Chapman & Hall/CRC The R Series)

Fundamentals of Supervised Machine Learning: With Applications in Python, R, and Stata (Statistics and Computing)

Statistical Theory: A Concise Introduction (Chapman & Hall/CRC Texts in Statistical Science)

The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)

Fundamentals of Supervised Machine Learning: With Applications in Python, R, and Stata (Statistics and Computing)

Machine Learning: Theory and Practice

Foundations of Statistical Algorithms: With References to R Packages (Chapman & Hall/CRC Computer Science & Data Analysis)

High-Dimensional Statistics: A Non-Asymptotic Viewpoint: 48 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 48)

Applied Machine Learning Using mlr3 in R

Modern Data Mining Algorithms in C++ and CUDA C: Recent Developments in Feature Extraction and Selection Algorithms for Data Science

Data Analytics: A Small Data Approach (Chapman & Hall/CRC Data Science Series)

Probability and Statistics for Computer Science

Computational Statistics in Data Science