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H**.
Fantastic intro to ML - focuses on core ideas with plenty of visuals
I got this book because I'm a fan of Josh's YouTube channel. He has a knack for explaining things well in a funny way, by using visuals, jokes, and helping see the intuition behind things.This book is in a similar style. It is driven by diagrams and funny cartoons, plus jokes that made me LOL a few times (like "SoftPlus" sounding like a toilet paper brand, and mentions of Troll 2).The book is mainly from a stats perspective: Josh helps you see modelling as fitting data (but not overfitting it), even in the case of neural networks.What does it actually cover? Some of the most important models in ML: linear models, logistic regression, SVMs, decision trees, Naive Bayes and neural networks.On top of that, Josh discusses stats and ML fundamentals and how to evaluate and adjust models: which includes cross-validation and gradient descent. Appendices have a quick intro to some of the other math topics (like calculating derivatives).Where this book really shines is in bringing home a good intuition of how ML actually works, thanks to the clear explanations and detailed diagrams. There is a focus on the "big ideas" instead of getting lost in the minutiae while not shying away from the math. It also shows repeated themes and tools used in the field (e.g. minimising a loss function and gradient descent).In summary, I think this book is great whether you are someone starting to learn about ML or even if you have more experience and want a nice refresher of the fundamentals in a quirky way.
A**Z
Best for visual learners
Amazing book. It does not oversimplify concepts, and uses the right terminology, but the explanations are so straight to the point and visual that it is impossible not to understand everything that's been explained. I bought it mainly because I have been following statquest videos in YouTube forever and they have taught me more than my own PhD courses have. The fact that the explanations are visual is a tremendous help for us visual learners. 10 out of 10. I will be purchasing the CNN one next month.
G**M
The best ML or Stats book
Makes complex maths so simple and straightforward. A huge compliment to the YouTube videos
M**N
Fabulous book for understanding
Simple explanations of complex mathematical principles and a great complement to the You Tube videos
N**Y
Wonderfully written, beautifully illustrated
I started reading this today. About 50 pages in an I'm impressed. It's written in such a concise, digestible manner whilst still maintaining a good degree of detail. The colours are pleasing to the eye and definitely help maintain your attention without being a distraction. My only criticism is I wish there was a hardback option available. I'm a PhD but also teach so would have loved to have been able to use this with my students as I often get questions about ML. I just don't feel comfortable taking this into the classroom as the backing feels a bit delicate compared to other paperbacks.
D**M
Great book, difficult to press on at times
I love Josh’s videos on YT, they have helped me immensely throughout my career as a Data Scientist. I bought this because I’m bought into his work and wanted to give something back and to refresh myself on the basics.The book is clear to follow once you get used to following the arrows around the pages, and covers machine learning, starting from the fundamentals such as p-values/R-squared, histograms - their uses and limitations, and then goes on to explain normal distributions etc, and finally getting to the good stuff that is linear & logistic regression, gradient descent and beyond. Each chapter builds on the previous and Josh repeats himself in a way that cements your understanding.My major gripe with this book, like many stats/ML books before it, is the same gripe that lead many people to tire of statistics in the classroom - the examples are so incredibly dull and uninspired. Distributions are taught using flavours of pie, linear regression is taught using models of height vs weight, logistic regression using popcorn vs movie enjoyment, and naive bayes is taught using the classic spam vs not spam email classifier. They aren’t interesting or memorable in the slightest.As an example - read Statistics Without Tears, the examples in that book are so much more interesting, and make it a page turner, whereas this books examples make it difficult to stay interested.The format of the book being lots of images with short descriptions and arrows to follow, while making it simple, also do it a disservice as I feel Josh could explain some concepts with a little bit more detail, such as where the terminology comes from, or fleshing out definitions a bit more comprehensively.I would still highly recommend this book, because the simplicity of the diagrams make it an excellent introduction to concepts you may have heard about, and the segway from basic statistics into ML is rarely mentioned in beginner books. For statistics alone I would partner this with Statistics Without Tears - read that, then this.
N**K
Easy to read
I bought this book after watching the Statquest YouTube vids. Very happy that I did, it is accessible and informative.It gives a great introduction to Ml. Would highly recommend 👌
T**E
Thats Stat!
Currently on a Data Analytics course and this has come in very handy..Great little illustrations to keep me occupied.Also the YouTube videos are a plus as well, if like me you need alternative ways of learning.
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