Sticky Post – Read this first. Categories and Links in Mathemafrica

The navigability of Mathemafrica isn't ideal, so I have created this post which might guide you to what you are looking for. Here are a number of different categories of post which you might like to take a look at: First year mathematics notes and resources (particularly for the University [...]

By | January 17th, 2018|0 Comments

Patterns, Predictions and Actions: Foundations of Machine Learning, by Hardt and Recht – a review

NB. I was sent this book as a review copy. From Princeton University Press I've just taught a course on mathematics for data science. Sadly it was only ten hours long, so there was only so much that I could cover. However, I feel that was taught was sufficient to [...]

By | January 29th, 2023|1 Comment

The Story of Proof: Logic and the History of Mathematics, by John Stillwell – a review

NB. I was sent this book as a review copy. From Princeton University Press The last book of Stillwell's that I reviewed was Reverse Mathematics which was utterly fascinating, and truly mind-bending. I was very much looking forward to another of his books, and this one did not disappoint. [...]

By | January 29th, 2023|1 Comment

THE BIG BANG OF NUMBERS. How to build the universe using only maths, by Manil Suri (Bloomsbury, 2022) – a review by Henri Laurie

Goodreads link. Oh no. Not another overview of mathematics, for “everyone”. Set theory, numbers from natural to complex, geometry, algebra. Axiomatics. Gödel. Infinity. Applications. Philosophy?? Isn’t this all a big yawn? Hasn’t this been done again and again? For example by Lancelot Hogben, Eric Temple Bell, Reuben Hersch (and that’s [...]

By | November 7th, 2022|0 Comments

The best writing on Mathematics, 2021, Edited by Mircea Pitici – a review

NB. I was sent this book as a review copy. From Princeton University Press I've been reading this series every year now for the last five years or so, and it never disappoints. Mircea does an amazing job each time at collecting such a diverse ideas, voices, and [...]

By | October 6th, 2022|0 Comments

On useful study habits

I've been teaching MAM1000W for around 9 years now, and I am learning all the time. I learn both about new ways to think about old subjects (and how to try and best explain them), and I learn about the way students study, about what works and what doesn't, and [...]

By | May 13th, 2022|2 Comments

In pursuit of Zeta-3 – The World’s Most Mysterious Unsolved Math Problem, by Paul Nahin – a review

NB. I was sent this book as a review copy. From Princeton University Press I have to admit that I felt very skeptical when I started reading this book. In the prologue it is stated that the book is aimed at enthusiastic readers of mathematics with an AP [...]

By | April 23rd, 2022|3 Comments

When least is best, by Paul Nahin – a review

NB. I was sent this book as a review copy. From Princeton University Press For my review of Nahin's superb book "How to fall slower than gravity", see here. While not often taught as a topic with such wide-ranging uses in maths classes, finding the maxima or minima [...]

By | April 23rd, 2022|1 Comment

A course in Complex Analysis, by Saeed Zakeri – a review

NB. I was sent this book as a review copy. From Princeton University Press This is a no-nonsense, clearly written graduate level textbook on complex analysis, and while it is written for a graduate audience, I think that the way it is laid out, with clear examples throughout, [...]

By | April 23rd, 2022|0 Comments

Visual Differential Geometry and Forms – a mathematical drama in five acts, by Tristan Needham – a review

NB. I was sent this book as a review copy. From Princeton University Press Studying physics, some two decades ago at The University of Bristol, I found the majority of what we covered relatively intuitive. Even the arcane world of quantum mechanics, while impossible to truly visualise, is, [...]

By | December 11th, 2021|0 Comments

CRL Task 5: Learning Causal Models

We've now come to one of the most vital aspects of this theory - how can we learn causal models? Learning models is often an exceptionally computationally intensive process, so getting this right is crucial. We now develop some mathematical results which guarantee bounds on our learning. We'll start by [...]

By | September 19th, 2021|0 Comments
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