Towards AI·2yThe Fundamental Mathematics of Machine Learning
This blog explores the core mathematical concepts essential for understanding and building machine learning models. It dives deep into linear algebra and calculus, highlighting their importance in model training and optimization. The post provides practical applications, case studies, and step-by-step examples to enhance your grasp of these foundational principles.
Hacker News·2yThe Math of Card Shuffling
A deck of cards needs to be riffle shuffled seven times to achieve a sufficiently random order. This is derived from the mathematical concept of permutations, considering a standard deck of 52 cards. Additionally, shuffling one card at a time would require an average of 236 single card riffles to completely randomize the deck. The post references a Numberphile video discussing these and other card shuffling facts.
KDnuggets·2yIntroduction to Statistics: A Statology Primer
A collection of tutorials from Statology, this primer covers essential introductory statistics concepts. It explores the importance of statistics, the difference between descriptive and inferential statistics, the distinction between population and sample, the terms statistic vs. parameter, and the types of qualitative and quantitative variables. It also describes the four levels of measurement scales: nominal, ordinal, interval, and ratio.
