Issue #183
November 27, 2022
This weeks Data Science Book is " Code: The hidden language of Computer Hardware and Software " by C. Petzold.This book is a bit of detour from our usual fare here at Data For Science as it focuses more on Computer Science than on Data Science per se . It provides a step-by-step timeline of how computers came to be, in a clear and concise way. It takes you on a tour of what happens "behind" the pixels on your screen, from logical gates on up, without requiring a heavy technical background. Chapter, by chapter, introduces each concept and technology necessary to make modern computers work. By the end of it, you'll have a detailed an intuitive understanding how Computers really work and will be able to mode easily optimize the way in which you write your own software. It might also make you want to learn to program in Assembly! A book that should be required reading for anyone interested in Computer Science.
- 1. The Computational Geometry Algorithms Library [cgal.org]
- 2. AWS and Blockchain [tbray.org]
- 3. Why Meta's latest large language model survived only three days online [technologyreview.com]
- 4. Good Machine Learning Practice for Medical Device Development: Guiding Principles [fda.gov]
- 5. CICERO: An AI agent that negotiates, persuades, and cooperates with people [ai.facebook.com]
- 6. The Principal Engineer's Handbook [ilya.grigorik.com]
- 7. The Physics of Scuba Diving [wired.com]
- • Human-level play in the game of Diplomacy by combining language models with strategic reasoning (Meta Fundamental AI Research Diplomacy Team (FAIR)
- • Cancer vaccines: the next immunotherapy frontier (M. J. Lin, J. Svensson-Arvelund, G. S. Lubitz, A. Marabelle, I. Melero, B. D. Brown, J. D. Brody)
- • Effective resistance against pandemics: Mobility network sparsification for high-fidelity epidemic simulations (A. Mercier, S. Scarpino, C. Moore)
- • Origin and destination attachment: study of cultural integration on Twitter (J. Kim, A. Sîrbu, F. Giannotti, G. Rossetti, H. Rapoport)
- • Simulation-Based Bayesian Analysis (M. Plummer)
- • Complex-Valued Autoencoders for Object Discovery (S. Löwe, P. Lippe, M. Rudolph, M. Welling)
- • Reconstruction of the temporal correlation network of all-cause mortality fluctuation across Italian regions: the importance of temperature and among-nodes flux (G. Gigante, A. Giuliani)
Apache Spark Tutorial Python With PySpark
All our videos are also available in our YouTube playlist.
Enjoy the newsletter?
Forward it to a friend, or subscribe to get it straight to your inbox.
Subscribe Free