From Curve Fitting to Machine Learning: An Illustrative Guide to Scientific Data Analysis and Computational Intelligence (Intelligent Systems Reference Library, 18) by Achim Zielesny (2011)

A user-friendly and visually informative manual for scientific data analysis and computational intelligence. Covers curve fitting, clustering, machine learning, as well as mathematical optimization and evolutionary algorithms. Concepts and ideas presented in a straightforward manner with visually supported plausibility arguments and basic mathematical explanations [Read More]

Machine Learning in the AWS Cloud by Abhishek Mishra (2019)

Put the power of AWS Cloud machine learning services to work in your business and commercial applications! Machine Learning in the AWS Cloud introduces readers to the machine learning (ML) capabilities of the Amazon Web Services ecosystem and provides practical examples to solve real-world regression and classification problems. [Read More]

Python Machine Learning for Beginners Learning from scratch NumPy, Pandas, Matplotlib, Seaborn, Scikitlearn, and TensorFlow by AI publishing (2021)

Python Machine Learning for Beginners Machine Learning (ML) and Artificial Intelligence (AI) have firmly established their presence. Based on substantial data and evidence, it’s clear that ML and AI are not just passing trends but integral to the future. [Read More]

Data science: The hard parts. Techniques for Execelling at Data Science by Daniel Vaughan (2023, O'Reilly)

This hands-on guide offers a set of techniques and best practices that are often missed in conventional data engineering and data science education. A common misconception is that great data scientists are experts in the “big themes” of the discipline, namely ML and programming. [Read More]

R-packages: Organize, Test, Document, and Share Your Code by by Hadley Wickham and Jennifer Bryan (2023, O'Reilly)

Welcome to R Packages by Hadley Wickham and Jennifer Bryan. Packages are the fundamental units of reproducible R code. They include reusable R functions, the documentation that describes how to use them, and sample data. [Read More]