Issue #188

D4S Sunday Briefing #188

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

​

Jan 2, 2023

Dear Friends,
​
Welcome to the first 2023 edition of the Sunday Briefing. This week we’re proud to announce our latest Medium post “Top 10 Books we read in 2022”. You can also catch up on our latest post on the G4Sci series: Network Attacks: Breaking up a network without observing it completely or the latest Viz4Sci in the series: Photo Color Scheme.

Several of you have reached out in recent weeks asking how they can help support the work we do here at Data For Science. While the Sunday Briefing is a labor of love and will always remain free, it is not without costs, and any help is appreciated.

If you wish to support our work, there are several options:

1. Paid subscription to Graphs for Science or Visualization for Science which gives you complete access to the archive of previous posts.
2. Subscribe to Medium using our referral link at no extra cost to you
3. Directly through a one-time PayPal donation.

The countdown to the very first edition of the Graphs for Data Science webinar is well underway, with just over 10 days to go! Register now so you don’t miss out!

We’re also proud to announce the next edition of the NLP For Everyone webinar coming up on Feb 21st, 2023. Register now, so you don’t miss your spot!

On our regularly scheduled content we learn about Building Airbnb Categories with ML and Human-in-the-Loop, explore an annotated History of Modern AI and Deep Learning , and how to backtest your Trading Systems with Python.

On the academic front, we learn how to use longitudinal data collection to follow social network and language development dynamics at preschool and how schooling substantially improves intelligence, but neither lessens nor widens the impacts of socioeconomics and genetics.

This week’s Data Science Book is “Data Science in Context” by A. Z. Spector, P. Norvig, C. Wiggins, and J. M. Wing. As always you can find all the previous book recommendations on our website. In the video of the week, we have “Matplotlib Animations in Python”

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

​This week’s Data Science Book is “Data Science in Context” by A. Z. Spector, P. Norvig, C. Wiggins, and J. M. Wing. The book, whose authors require no introduction, provides a comprehensive overview of Data Science, covering the technical aspects of the field and the ethical considerations and challenges it presents. It is structured in a way that makes it easy for readers to understand and absorb the information and offers recommendations for addressing ethical concerns. The authors focus on real-life examples from their various fields, such as healthcare and finance, to illustrate data science applications and their potential impact. Aimed at a wide audience, that includes data science novices and experienced professionals, and is recommended for anyone with an interest in data science and its role in daily life and various industries.

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

1. ​Building Airbnb Categories with ML and Human-in-the-Loop [medium.com/airbnb-engineering]
2. ​Annotated History of Modern AI and Deep Learning [people.idsia.ch/~juergen]
3. ​Backtest your Trading Systems with Python — Plotting [wire.insiderfinance.io]
4. ​Top Python libraries of 2022 [tryolabs.com]
5. ​Ready-to-go sample data pipelines with Dataflow [netflixtechblog.com]
6. ​Hands-on Generative Adversarial Networks (GAN) for Signal Processing, with Python [towardsdatascience.com]
7. ​7 Visualizations with Python to Express Changes in Rank over Time [towardsdatascience.com]

Some of the most interesting academic papers published recently

• ​Longitudinal data collection to follow social network and language development dynamics at preschool (S. Dai, H. Bouchet, M. Karsai, J.-P. Chevrot, E. Fleury, A. Nardy)
• ​Genomics and phenomics of body mass index reveals a complex disease network (J. Huang, J. E. Huffman, Y. Huang, Í. Do Valle, T. L. Assimes, S. Raghavan, B. F. Voight, C.-M. Liu, A.-L. Barabási, et al)
• ​Reversibility of link prediction and its application to epidemic mitigation (S. Sulaimany, A. Mafakheri)
• ​Schooling substantially improves intelligence, but neither lessens nor widens the impacts of socioeconomics and genetics (N. Judd, B. Sauce, T. Klingberg)
• ​Public Health and Online Misinformation: Challenges and Recommendations (B. Swire-Thompson, D. Lazer)
• ​Identifying Influential Spreaders in Complex Networks Based on Degree Centrality (Q. Wang, J. Ren, H. Zhang, Y. Wang, B. Zhang)
• ​A meso-scale cartography of the AI ecosystem (F. Gargiulo, S. Fontaine, M. Dubois, P. Tubaro)

​Matplotlib Animations in Python

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

Upcoming Events

Opportunities to learn from us:

1. Jan 10, 2023 — Graphs for Data Science 🆕 [Register]
2. Feb 21, 2023 — NLP For Everyone 🆕 [Register]

On-demand videos

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.

Read all stories on Medium and help support my work by subscribing through my link: https://bgoncalves.medium.com/membership