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D4S Sunday Briefing #163
A weekly newsletter with the latest developments in Data Science and Machine Learning and Artificial Intelligence.
Jul 10, 2022
Welcome to the July 10th edition of the Sunday Briefing. This week we’re proud to announce our latest blog post: Mandelbrot Set: Using ConnectionPatch to connect subplots in the V4Sci series. 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.
While on the more academic front we look at how Central bank digital currencies risk are becoming a digital Leviathan, a review of Blockchain Governance, fast computation of rankings from pairwise comparisons and Collective Memory in the Digital Age.
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 a lecture on the Art of Code by Dylan Beattie.
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The D4S Team
The latest post on the Visualization for Data Science substack: Mandelbrot Set: Using ConnectionPatch to connect subplots 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.
- AI Forecasting: One Year In [bounded-regret.ghost.io]
- What is Machine Learning Anyway? [dockyard.com]
- Historical weather for machine learning [openmeteo.substack.com]
- On Turing machines [lawrencecpaulson.github.io]
- How CUDA Programming Works [nvidia.com]
- Advanced SQL Concepts You Should Know in 2022 [towardsdatascience.com]
- AI-Powered Algorithmic Trading with Python [odsc.medium.com]
Some of the most interesting academic papers published recently
- Central bank digital currencies risk becoming a digital Leviathan (A. Baronchelli, H. Halaburda, A. Teytelboym)
- SoK: Blockchain Governance (A. Kiayias, P. Lazos)
- A Majority-Vote Model On Multiplex Networks with Community Structure (K. Peng, M. A. Porter)
- Semi-Supervised Hierarchical Graph Classification (J. Li, Y. Huang, H. Chang, Y. Rong)
- Fast computation of rankings from pairwise comparisons (M. E. J. Newman)
- Collective Memory in the Digital Age (T. Yasseri, P. Gildersleve, L. David)
- Language statistics at different spatial, temporal, and grammatical scales (F. Sánchez-Puig, R. Lozano-Aranda, D. Pérez-Méndez, E. Colman, A. J. Morales-Guzmán, C. Pineda, C. Gershenson)
Interesting discussions, ideas or tutorials that came across our desk
The Art of Code
All the videos of the week are now available in our Youtube playlist.
Opportunities to learn from us:
- Jul 26, 2022 — Time Series for Everyone [Register] 🆕
- Aug 9, 2022 — Advanced Time Series for Everyone [Register] 🆕
- Aug 25, 2022 — Natural Language Processing 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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