Teens surprise math world with Pythagorean Theorem trigonometry proof

 

 

 

 

2024-03-31 Sunday - Interesting Math Books

 

All the Math You Missed: (But Need to Know for Graduate School) 2nd Edition 

"Beginning graduate students in mathematical sciences and related areas in physical and computer sciences and engineering are expected to be familiar with a daunting breadth of mathematics, but few have such a background. This bestselling book helps students fill in the gaps in their knowledge. Thomas A. Garrity explains the basic points and a few key results of all the most important undergraduate topics in mathematics, emphasizing the intuitions behind the subject. The explanations are accompanied by numerous examples, exercises and suggestions for further reading that allow the reader to test and develop their understanding of these core topics. Featuring four new chapters and many other improvements, this second edition of All the Math You Missed is an essential resource for advanced undergraduates and beginning graduate students who need to learn some serious mathematics quickly."

(image source: Amazon.com)

 

Mathematics for Machine Learning (2020) 

https://www.amazon.com/Mathematics-Machine-Learning-Peter-Deisenroth/dp/110845514X/

https://mml-book.github.io/book/mml-book.pdf
Companion webpage to the book "Mathematics for Machine Learning". Copyright 2020 by Marc Peter Deisenroth, A. Aldo Faisal, and Cheng Soon Ong. Published by Cambridge University Press.

"The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site."

(image source: Amazon.com)

 

 

 

 

 

 

Statistical Inference A Work in Progress (~2019)

Statistical Inference A Work in Progress (~2019)
Ronald Christensen
Department of Mathematics and Statistics, The University of New Mexico
https://stat.unm.edu/~fletcher/INFER.pdf

Book: The Simpsons and Their Mathematical Secret

[image source: Amazon.com]

 

https://www.amazon.com/Simpsons-Their-Mathematical-Secrets/dp/1620402785

Simon Singh, author of the bestsellers Fermat's Enigma, The Code Book, and Big Bang, offers fascinating new insights into the celebrated television series The Simpsons: That the show drip-feeds morsels of number theory into the minds of its viewers―indeed, that there are so many mathematical references in the show, and in its sister program, Futurama, that they could form the basis of an entire university course.

Recounting memorable episodes from "Bart the Genius" to "Homer3," Singh brings alive intriguing and meaningful mathematical concepts―ranging from the mathematics of pi and the paradox of infinity to the origin of numbers and the most profound outstanding problems that haunt today's generation of mathematicians. In the process, he illuminates key moments in the history of mathematics, and introduces us to The Simpsons' brilliant writing team―the likes of David X. Cohen, Al Jean, Jeff Westbrook, and Stewart Burns―all of whom have various advanced degrees in mathematics, physics, and other sciences.

Based on interviews with the writers of The Simpsons and replete with images from the shows, facsimiles of scripts, paintings and drawings, and other imagery, The Simpsons and Their Mathematical Secrets will give anyone who reads it an entirely new insight into the most successful show in television history.

Kasper Müller

https://www.linkedin.com/in/kasper-m%C3%BCller-96ba95169/

https://kaspermuller.medium.com/

• Editor, Cantor's Paradise 
• Senior Consultant, Data and Analytics, FS, Technology Consulting, EY
  

The Beauty and Power of Discrete Calculus
https://www.cantorsparadise.com/the-beauty-and-power-of-discrete-calculus-87931daa074

 

nⁿ+(n+1)ⁿ Primes

https://www.linkedin.com/feed/update/urn%3Ali%3Aactivity%3A6968197862727790593/

"The only known primes of shape nⁿ+(n+1)ⁿ are 3, 13 and 881."

Google Cloud Calculates Pi To 100 Trillion Digits

Google Cloud Calculates Pi To 100 Trillion Digits

• https://science.slashdot.org/story/22/06/09/0128234/google-cloud-calculates-pi-to-100-trillion-digits
• https://www.engadget.com/google-cloud-pi-100-trillion-digits-174908346.html
• https://blog.google/products/google-cloud/new-digit-pi-2022/

"Google Cloud developer advocate Emma Haruka Iwao and her colleagues say they've calculated Pi to 100 trillion digital decimal places." 

"Iwao and her team previously set the record in 2019 when they carried out a calculation to an accuracy of 31.4 trillion digits." 

"In 2019, the calculation (which figured out a third as many digits as the most recent attempt) took 121 days. This time around, the calculation ran for 157 days, 23 hours, 31 minutes and 7.651 seconds, meaning the computers were running more than twice as quickly despite Iwao using "the same tools and techniques." Around 82,000 terabytes of data were processed overall. Iwao also notes that reading all 100 trillion digits out loud at a rate of one per second would take more than 3.1 million years. And in case you're wondering, the 100-trillionth decimal place of Pi is 0."