There are plenty of resources on the Internet to learn linear algebra or to get a refresher, including our own tutorial (here). Below are three interesting books found on Amazon.  Linear Algebra: Step by Step The strength of the text is in the large number…

290+ Machine Learning Projects Solved & Explained using Python programming language.

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We study how researchers can apply machine learning (ML) methods in finance. We first establish that the two major categories of ML (supervised and unsupervised

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What are the predictions for artificial intelligence in 2023? We speak to 5 experts about how AI is going to be adopted over the coming year

Statistical errors are common in scientific literature and about 50% of the published articles have at least one error. The assumption of normality needs to be checked for many statistical procedures, namely parametric tests, because their validity depends…

Normality tests can be classified into tests based on chi-squared, moments, empirical distribution, spacings, regression and correlation and other special tests. This paper studies and compares th...

🧮 A collection of resources to learn mathematics for machine learning - dair-ai/Mathematics-for-ML

You read documentation and tutorials to become a better programmer, but if you really want to be cutting-edge, academic research is where it's at.

How did complex systems emerge from chaos? Physicist Sean Carroll explains.

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Plain python implementations of basic machine learning algorithms - zotroneneis/machine_learning_basics

A deep dive into the mathematics and the intuition of diffusion models. Learn how the diffusion process is formulated, how we can guide the diffusion, the main principle behind stable diffusion, and their connections to score-based models.