81–90 of 281 posts
CA is a tough discipline to understand in my experience; the endless nuance and relativism is hard to hold in your mind and not get lost in ‘vagueness’. This is a great read to understand the field a lot better. It’s used in introductory classes at least all over Europe.
Global Shift by Peter Dicken. ...Mind expanding....
Widely adopted throughout the world, this definitive text comprehensively examines how the global economy works and its effects on people and places. Peter Dicken provides a balanced yet critical analysis of globalization processes and debates.
Here is one compiled list of answers: https://www.lesswrong.com/posts/xg3hXCYQPJkwHyik2/the-best-t... One nice thing about this list is that every recommendation must be accompanied by a few books not recommended. I think this request helps prevent well-meaning non-experts pollute the list with books from smaller reading pools.
Options, Futures and Other Derivatives is basically a Bible. https://www.amazon.com/gp/aw/d/013447208X/ref=dp_ob_neva_mob...
On interest rates and yield curves, a book I would recommend is Sadr’s Interest Rates Swaps and their Derivatives [1]. Unfortunately it is a bit dated and a lot happened since it was written. But it is a very good book to understand interest rate models, which focuses more on the intuition and practical aspects and which I think is a lot more useful to a professional.
[1] https://www.amazon.com/Interest-Rate-Swaps-Their-Derivatives...
As a chemical engineer (many of these go beyond the undergraduate level): 1) The principles of chemical equilibrium, by Kenneth George Denbigh 2) Mass Transfer by Sherwood 3) Process Dynamics, Modeling, and Control by Babatunde Ogunnaike and W. Harmon Ray 4) Chemical Process Industries by Shreeves 5) An Introduction to Numerical Methods and Analysis by James F. Epperson 6) Optimization: Theory and Practice by Gordon…
[0] (https://en.m.wikipedia.org/wiki/Perry's_Chemical_Engineers'_...)
Nevermind pathophysiology, this textbook teaches the art of interacting with patients.
In machine learning, hands down these are some of the best related textbooks: - [0] Pattern Recognition and Machine Learning (Information Science and Statistics) and also: - [1] The Elements of Statistical Learning - [2] Reinforcement Learning: An Introduction by Barto and Sutton - [3] The Deep Learning by Aaron Courville, Ian Goodfellow, and Yoshua Bengio - [4] Neural Network Methods for Natural Language Processing…
I have to disagree with The Deep Learning book. I don't find it a good book for anyone. For beginners it's too advanced/theoretical and for experienced ML scientists it's entirely too basic. I very much agree with this review on Amazon [1]. For the former, I would recommend Hands-On Learning with Scikit-Learn and Tensorflow [1] https://www.amazon.com/gp/customer-reviews/R1XNPL1BX5IVOM/re...
As a scientist coming to deep learning from another field, I found Courville et al to be pitched at the perfect level.
https://en.wikipedia.org/wiki/PiHKAL https://en.wikipedia.org/wiki/TiHKAL
Options, Futures and Other Derivatives is basically a Bible. https://www.amazon.com/gp/aw/d/013447208X/ref=dp_ob_neva_mob...