Issue #195

March 21, 2023

This week’s Data Science Book is “ Introduction to Algorithms (4th edition) ” by T. M. Cormen, C. E. Leiderson, R. L. Rivest and C. Stein. This book is affectionately known as the bible of algorithms and over the years has proven to be an essential reading and, at over 1300 pages, a complete reference for anyone interested in gaining a broad understanding of algorithms. The content can at times be challenging but is presented in a fashion that is engaging and easily digestible. Exercises at the end of each chapter are expressly presented without the benefit of solutions but were carefully designed to help students to think algorithmically and thoroughly absorb the material presented.

Introduction to Algorithms (4th edition)

1. Automatic Image Mining [blog.qwertyforce.dev]
2. What is Temperature in NLP? [lukesalamone.github.io]
3. A SQLite extension which loads a Google Sheet as a virtual table [github.com/0x6b]
4. A brief guide to Kubernetes networking [ergomake.dev]
5. Python-based compiler achieves orders-of-magnitude speedups [news.mit.edu]
6. Maybe Bitcoin NFTs Are a Mistake [somereverie.substack.com]
7. The Unpredictable Abilities Emerging From Large AI Models [quantamagazine.org]

• Evolutionary-scale prediction of atomic-level protein structure with a language model (Z. Lin, H. Akin, R. Rao, B. Hie, Z. Zhu, W. Lu, N. Smetanin, R. Verkuil, O. Kabeli, Y. Shmueli, A. Dos Santos Costa, M. Fazel-Zarandi, Tom Sercu, S. Candido, A. Rives)
• On the forecastability of food insecurity (P. Foini, M. Tizzoni, G. Martini, D. Paolotti, E. Omodei)
• Spread of networked populations is determined by the interplay between dispersal behavior and habitat configuration (B. Rayfield, C. B. Baines, L. J. Gilarranz, A. Gonzalez)
• Modern language models refute Chomsky’s approach to language (S. Piantadosi)
• Fast approach for link prediction in complex networks based on graph decomposition (A. Saifi, F. Nouioua, S. Akhrouf)
• EPIGUI: Graphical User Interface for Simulating Epidemics on Networks (E. R. Pinto, E. G. Nepomuceno, J. Kusak, A. S. L. O. Campanharo)
• Linking social network structure and function to social preferences (J. B. Brask, A. Koher, D. P. Croft, S. Lehmann)
• Strong, weak or no balance? Testing structural hypotheses against real networks (A. Gallo, D. Garlaschelli, R. Lambiotte, F. Saracco, T. Squartini)

How to make Animated plot with Matplotlib and Python

March 21, 2023

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