Issue #117

July 4, 2021

This weeks Data Science Book is the most excellent "Feynman's Lectures on Computation" by R. P. Feynman. You might be familiar with Feynman's Lectures on Physics, but his lectures on Computation (based on a class he taught and his work in 'Connection Machine') aren't any less amazing. Through this short book, Feynman guides us through the concept of computation and the van Neumann architecture in his unique style, from logic functions, to Turing machines, coding and even quantum computers. While not directly related to Data Science, it will give you a unique appreciation of the finer points in which computers are "Dumb as hell but go like mad" so that you can better squeeze every bit of performance out of your code.

Feynman's Lectures on Computation

1. An Overview of Dataviz for Categorical Data [nightingaledvs.com]
2. Systems for Machine Learning [thegradient.pub]
3. Complete guide to understanding Node2Vec algorithm [towardsdatascience.com]
4. Machine learning’s crumbling foundations [doctorow.medium.com]
5. How Big Data Carried Graph Theory Into New Dimensions [quantamagazine.org]
6. Computer Scientists Discover Limits of Major Research Algorithm [quantamagazine.org]
7. Algorithms Are the Matter [adamjuliangoldstein.com]
8. Learning to Extrapolate with Generative AI Models [blog.einstein.ai]

• A modified DeepWalk method for link prediction in attributed social network (K. Berahmand, E. Nasiri, M. Rostami, S. Forouzandeh)
• Inference of stochastic time series with missing data (S. Lee, V. Periwal, J. Jo)
• Why temporal networks are more controllable: Link weight variation offers superiority (X.-Y. Zhang, J. Sun, G. Yan)
• Social network analysis for social neuroscientists (E. C. Baek, M. A. Porter, C. Parkinson)
• On the Opportunities and Risks of Foundation Models (R. Bommasani, D. A. Hudson, E. Adeli, R. Altman, S. Arora, S. von Arx, M. S. Bernstein, J. Bohg, A. Bosselut, E. Brunskill, E. Brynjolfsson, S. Buch, D. Card, R. Castellon, N. Chatterji, A. Chen, K. Creel, J. Q. Davis, D. Demszky, C. Donahue, et al)
• Data Visualization: A practical introduction (K. Healy)
• Successive cohorts of Twitter users show increasing activity and shrinking content horizons (F. Wolf, P. Lorenz-Spreen, S. Lehmann)
• Infusing Culture in Compartmental Epidemic Models (E. E. Santos, J. Korah, S. Subramanian, V. Murugappan, E. Santos)
• Mobile Phone Location Data for Disasters: A Review from Natural Hazards and Epidemics (T. Yabe, N. K. W. Jones, P. S. C. Rao, M. C. Gonzalez, S. V. Ukkusuri)

Advanced NLP with spaCy

July 4, 2021

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