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Issue #143

A weekly newsletter with the latest developments in Data Science and Machine Learning and Artificial Intelligence.​

Bruno Gonçalves

Dear Friends,

Welcome to the Feb 20th edition of the Sunday Briefing.

This week we’re on hiatus from blogging but feel free to catch up on our recent posts. We have just published Epidemic Models: the role of degree correlations on the Graphs for Science Substack, while on Medium we have a recap of the Top 10 Books we read in 2021. Finally, on the Visualization for Science substack we take a dive into matplotlib animations with the Christmas Tree Animation post.

On Friday, Feb 25th we have the next installment of the Deep Learning from Scratch webinar series. There’s still a few spots left so don’t miss out!

On our regularly scheduled content we have the House of Graph — a database of interesting graphs, an introduction to automated reasoning by the good folk over at Amazon, a look at how to perform Faster Python calculations with Numba and Static B-Trees.

From the Ivory Tower, we have an analysis of how to quantify NFT-driven networks in crypto art, visual object categorization in infancy and Outbreak Size Distribution in Stochastic Epidemic Models.

This weeks ‘Data Science Book’ highlight is Data Science Book is “Interactive Dashboard and Data Apps with Plotly and Dash” by E. Dabbas. As always you can find all the previous book recommendations on our website. In the video of the week we have a documentary on the history of Kubernetes.

Data shows that the best way for a newsletter to grow is by word of mouth, so if you think one of your friends or colleagues would enjoy this newsletter, just go ahead and forward this email to them. This will help us spread the word!

Semper discentes,

The D4S Team

The latest post on the Graphs for Data Science substack: Epidemic Models: the role of degree correlations is now out.You should Sign Up to make sure you never miss a post!

The latest post on the Visualization for Data Science substack: Christmas Tree Animation is now out, Don’t forget to Subscribe so you’re first in line to receive every 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:

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:

​This weeks Data Science Book is “Interactive Dahsboard and Data Apps with Plotly and Dash” by E. Dabbas. In our lives as data scientists and machine learning engineers, we are often called upon to develop Dashboards and other Data Drive apps to communicate results or to monitor the performance of models deployed to production. Plotly and Dash are the current State of the Art libraries for interactive visualizations with a web frontend. This book does a remarkable job of getting you up to speed with both of these libraries taking you from basic to advanced level through practical building blocks that you can immediately customize for your own use.

(affilate link)

Tutorials and blog posts that came across our desk this week.

  1. The House of Graphs []
  2. A gentle introduction to automated reasoning []
  3. Faster Python calculations with Numba []
  4. AI Overcomes Stumbling Block on Brain-Inspired Hardware []
  5. Static B-Trees []
  6. Include diagrams in your Markdown files with Mermaid []
  7. The Unreasonableness of Math is Context Independence []
  8. A deceptively simple plotting library for Streamlit []

Some of the most interesting academic papers published recently

Interesting discussions, ideas or tutorials that came across our desk.

Kubernetes: The Documentary

All the videos of the week are now available in our Youtube playlist.​

Opportunities to learn from us:

  1. Feb 25, 2022 — Deep Learning for Everyone [Register]
  2. Mar 04, 2022 — Time Series for Everyone [Register]
  3. Mar 07, 2022 — Advanced Time Series for Everyone [Register]
  4. Apr 20, 2022 — Natural Language Processing (NLP) for Everyone [Register] 🆕
  5. Apr 27, 2022 — NLP with Deep Learning for Everyone [Register] 🆕

Long form tutorials:

  1. Natural Language Processing 5.5h, covering basic and advancing techniques using NLTK and Keras
  2. Times Series Analysis for Everyone 6h covering data pre-processing, visualization, ARIMA, ARCH and Deep Learning models

Thank you for subscribing to our weekly newsletter with a quick overview of the world of Data Science and Machine Learning. Please share with your contacts to help us grow!

Publishes on Sunday.​

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