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🥂🍾 D4S Sunday Briefing #158 🍾🥂
A weekly newsletter with the latest developments in Data Science and Machine Learning and Artificial Intelligence.
Jun 04, 2022
Welcome to the 158th edition of the Sunday Briefing. The very first issue of the Sunday Briefing went out on Jun 3rd 2019 and we have a month long celebration of our third anniversary, starting with a facelift!
This week we’re on hiatus from blogging, but you can still catch up on our recent posts. First, we celebrate World Goth Day with the latest V4Sci post “Unknown Pleasures Plot: Recreating an iconic album cover and your favorite 80s t-shirt”. Over at Medium, we have “Exploring the Dow-Jones Industrial Average using Linear Regression”. You can also catch up on the latest post in the G4Sci series: Prim’s Minimum Spanning Tree Algorithm: Finding the shortest path to every node.
This coming Tuesday, Jun 7th we have the latest iteration of our Graphs and Network Algorithms for Everyone webinar. You’ll find it particularly useful if you follow our Graphs for Data Science substack. We still have a few open slots so don’t miss out.
On our regularly scheduled content we discuss the Doctoral Thesis of David Hilbert, learn about the Financial Pattern Recognition in Python and explore how to determine causality in correlated time series.
While on the more academic front we have a look at how Artificial intelligence is breaking patent law, the latent structure of global scientific development and move toward understanding the use of centralized exchanges for decentralized cryptocurrency.
This weeks ‘Data Science Book’ highlight is Data Science Book is “Analytical Skills for AI & Data Science” by D. Vaughan. As always you can find all the previous book recommendations on our website. In the video of the week we have an Introduction to Plotly Data Visualization.
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The D4S Team
The latest post on the Visualization for Data Science substack: Unknown Pleasures Plot: Recreating an iconic album cover and your favorite 80s t-shirt is now out, Don’t forget to Subscribe so you’re first in line to receive every post.
The latest post on the Graphs for Data Science substack: Prim’s Minimum Spanning Tree Algorithm: Finding the shortest path to every node is now out.You should Sign Up to make sure you never miss a post!
The latest post in the CoVID-19 series, ‘How to model the effects of vaccination’ takes a look at how simple modifications of the SIR model can help us better understand how vaccines work. As usual, all the code is available in GitHub: http://github.com/DataForScience/Epidemiology101
The latest post in the Causality series covers section ‘3.7 — Mediation’, a recipe to calculate the controlled directed effect. The code for each blog post in this series is hosted by a dedicated GitHub repository: https://github.com/DataForScience/Causality
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.
Tutorials and blog posts that came across our desk this week.
- On the Doctoral Thesis of David Hilbert [cantorsparadise.com]
- Compact word vectors with Bloom embeddings [explosion.ai]
- Best Practices for Deploying Language Models [txt.cohere.ai]
- Financial Pattern Recognition in Python [kaabar-sofien.medium.com]
- A Survey of Causal Inference Applications at Netflix [netflixtechblog.com]
- Meet Kryptology: Coinbase’s Open Source Cryptography Library [blog.coinbase.com]
- Determining causality in correlated time series [amazon.science]
Some of the most interesting academic papers published recently
- 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)
Interesting discussions, ideas or tutorials that came across our desk
Introduction to Plotly Data Visualization
All the videos of the week are now available in our Youtube playlist.
Opportunities to learn from us:
- Jun 07, 2022 — Graphs and Network Algorithms for Everyone [Register] 🆕
- Jun 23, 2022 — Why and What If — Causal Analysis for Everyone [Register] 🆕
Long form tutorials:
- Natural Language Processing 5.5h, covering basic and advancing techniques using NLTK and Keras
- Times Series Analysis for Everyone 6h covering data pre-processing, visualization, ARIMA, ARCH and Deep Learning models
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