Price loading...

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

Econometrics

Price data last checked 108 day(s) ago - refreshing...

View at Amazon

Price History & Forecast

No Price Data Available

Price history will appear here once data is collected from Amazon.

Price Distribution

No price data available for histogram

Description

This book presents the fundamental theoretical notions of supervised machine learning along with a wide range of applications using Python, R, and Stata. It provides a balance between theory and applications and fosters an understanding and awareness of the availability of machine learning methods over different software platforms. After introducing the machine learning basics, the focus turns to a broad spectrum of topics: model selection and regularization, discriminant analysis, nearest neighbors, support vector machines, tree modeling, artificial neural networks, deep learning, and sentiment analysis. Each chapter is self-contained and comprises an initial theoretical part, where the basics of the methodologies are explained, followed by an applicative part, where the methods are applied to real-world datasets. Numerous examples are included and, for ease of reproducibility, the Python, R, and Stata codes used in the text, along with the related datasets, are available online. The intended audience is PhD students, researchers and practitioners from various disciplines, including economics and other social sciences, medicine and epidemiology, who have a good understanding of basic statistics and a working knowledge of statistical software, and who want to apply machine learning methods in their work.

Product Specifications

Format: paperback
ASIN: 3031413393
Category: Books > Subjects > Business, Finance & Law > Economics > Econometrics
Domain: Amazon UK
Release Date: 15 November 2024
Listed Since: 16 November 2024

Barcode

No barcode data available

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

Price History & Forecast

No Price Data Available

Price Distribution

Description

Product Specifications

Barcode

Similar Products You Might Like

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

Applied Statistical Learning: With Case Studies in Stata (Statistics and Computing)

Applied Statistical Learning: With Case Studies in Stata (Statistics and Computing)

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

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

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

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

Statistical Learning from a Regression Perspective (Springer Texts in Statistics)

Statistical Learning from a Regression Perspective (Springer Texts in Statistics)

Statistics for Machine Learning: Techniques for exploring supervised, unsupervised, and reinforcement learning models with Python and R

Machine Learning: A Practical Approach on the Statistical Learning Theory

Data Science and Predictive Analytics: Biomedical and Health Applications using R (The Springer Series in Applied Machine Learning)

Data Science and Predictive Analytics: Biomedical and Health Applications using R (The Springer Series in Applied Machine Learning)

Machine Learning with R

Applied Machine Learning

Machine Learning Foundations: Volume 1: Supervised Learning

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

Machine Learning Methods

Machine Learning with Python: Theory and Implementation

Fundamentals and Methods of Machine and Deep Learning: Algorithms, Tools, and Applications

Bayesian Statistical Modeling with Stan, R, and Python

Bayesian Statistical Modeling with Stan, R, and Python

Data Science Concepts and Techniques with Applications

Python for Probability, Statistics, and Machine Learning