Issue #169
August 21, 2022
This weeks Data Science Book is "Fundamentals of Data Engineering" by J. Reis and M. Housley. While our focus is on Data Science, we can't downplay the major role played by Data Engineering in practical Data projects. In this recent tome, the authors guide us through the thought processes, concepts and principles necessary to establish a successful Data Engineering operation to help support all of your data driven projects. They recommend a cloud first approach that allows for quick experimentation, adaptation and scaling.
- 1. The Science of Scientific Writing [americanscientist.org]
- 2. The world map that reboots your brain [axbom.com]
- 3. Running Large-Scale Graph Analytics with Memgraph and NVIDIA cuGraph Algorithms [developer.nvidia.com]
- 4. Ethereum's "Merge" is about to put every ether miner out of work [arstechnica.com]
- 5. Vector search just got up to 10x faster, easier to set up, and vertically scalable [pinecone.io]
- 6. Comparing quantiles at scale in online A/B-testing [engineering.atspotify.com]
- 7. Text Embeddings Visually Explained [txt.cohere.ai]
- 8. What Would a Theory of Data Visualization Look Like? [filwd.substack.com]
- 9. Variational Auto Encoder (VAE) for the Numerai Dataset [medium.com/mlearning-ai]
- 10. From ML Model to ML Pipeline [towardsdatascience.com]
- • American cultural regions mapped through the lexical analysis of social media (T. Louf, B. Gonçalves, J. J. Ramasco, D. Sanchez, J. Grieve)
- • Using a cognitive network model of moral and social beliefs to explain belief change (J. Dalege, T. Van Der Does)
- • A spatiotemporal decay model of human mobility when facing large-scale crises (W. Li, Q. Wang, Y. Liu, M. L. Small, J. Gao)
- • Heterogeneous rarity patterns drive price dynamics in NFT collections (A. Mekacher, A. Bracci, M. Nadini, M. Martino, L. Alessandretti, L. M. Aiello, A. Baronchelli)
- • Information theory: A foundation for complexity science (A. Golan, J. Harte)
- • Impact of Lifting School Masking Requirements on Incidence of COVID-19 among Staff and Students in Greater-Boston Area School Districts: A Difference-in-Differences Analysis (T. L. Cowger, J. Clarke, E. J. Murray, S. M. Sánchez, M.T. Bassett, B. O. Ojikutu, N. Linos, K. T. Hall)
- • Knowledge graph embedding by projection and rotation on hyperplanes for link prediction (T. Le, N. Huynh, B. Le)
All the videos of the week are now available in ourYoutube playlist.
All our videos are also available in our YouTube playlist.
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