Issue #158
June 5, 2022
This weeks Data Science Book is " Analytical Skills for AI & Data Science " by D. Vaughan. This is an unusual book that takes a holistic approach to AI and Data Science from a Business perspective. Aimed at managers with limited Data Science experience, this book uses increasingly complex practical examples to introduce a wide range of concepts and analytical techniques. Even if you have no direct interest in AI and Data Science, this book will give you enough background knowledge to be able to successfully manage Data Scientists, break down complex problems into individual components and help guide your team towards the right solution to your business problems.
- 1. On the Doctoral Thesis of David Hilbert [cantorsparadise.com]
- 2. Compact word vectors with Bloom embeddings [explosion.ai]
- 3. Best Practices for Deploying Language Models [txt.cohere.ai]
- 4. Financial Pattern Recognition in Python [kaabar-sofien.medium.com]
- 5. A Survey of Causal Inference Applications at Netflix [netflixtechblog.com]
- 6. Meet Kryptology: Coinbase’s Open Source Cryptography Library [blog.coinbase.com]
- 7. Determining causality in correlated time series [amazon.science]
- • Analysis of 6.4 million SARS-CoV-2 genomes identifies mutations associated with fitness (F. Obermeyer, M. Jankowiak, N. Barkas, S. F. Schaffner, J. D. Pyle, L. Yurkovetskiy, M. Bosso D. J. Park M. Babadi, B. L. Macinnis, J. Luban, P. C. Sabeti, J. E. Lemieux)
- • The latent structure of global scientific development (L. Miao, D. Murray, W.-S. Jung, V. Larivière, C. R. Sugimoto, Y.-Y. Ahn)
- • Artificial intelligence is breaking patent law (A. George, T. Walsh)
- • Addressing delayed case reporting in infectious disease forecast modeling (L. J. Beesley, D. Osthus, S. Y. Del Valle)
- • Impact of vaccine hesitancy on secondary COVID-19 outbreaks in the US: an age-structured SIR model (A. de Miguel-Arribas, A. Aleta, Y. Moreno)
- • Toward Understanding the Use of Centralized Exchanges for Decentralized Cryptocurrency (Z. Zhou, B. Shen)
- • Network Cards: concise, readable summaries of network data (J. Bagrow, Y.-Y. Ahn)
Introduction to Plotly Data Visualization
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