Machine Learning Tricks, Learning with ChatGPT, and Other Recent Must-Reads
As August comes to a close, many of our readers are heading back to school (be it at university, a boot camp, or online), while others are shaking off the last vestiges of slower summer schedules. What better time to prepare for the next chapter of your data science learning journey?
If you’re just tuning in again to data- and ML-related topics, you’re in for a treat: many of our authors certainly did not slow down in the past month, and in fact were hard at work on some of their strongest articles to date. To kick off a new month (and bid a proper farewell to the previous one), we’ve collected our most popular articles from August for you to browse, bookmark, and — we hope—sink your teeth into. Enjoy!
Our most-read posts
The wisdom of crowds might not always be infallible, but you can’t go wrong with any of this month’s greatest hits on TDS—out of the hundreds of articles we’ve published, these were the ones that resonated most strongly with our (extremely) savvy readers.
- 130 ML Tricks and Resources Curated Carefully from 3 Years
A massive compendium of bite-sized nuggets of useful, digestible insights, carefully compiled by Bex T.. - How I Would Learn Data Science with ChatGPT (If I Could Start Over)
From Natassha Selvaraj, a practical roadmap for learning data science on your own with the aid of a certain chatbot. - How to Chat With Any PDFs and Image Files Using Large Language Models — With Code
For anyone who wants to get some hands-on experience working with LLMs, Zoumana Keita’s tutorial is a top-notch choice. - Graph Convolutional Networks: Introduction to GNNs
If you’re in the mood for an article with a perfect balance of theory and practice, look no further than Maxime Labonne’s accessible primer on GNNs. - Mastering Monte Carlo: How to Simulate Your Way to Better Machine Learning Models
Proving that a well-executed article can never be too long, Sydney Nye’s deep dive into Monte Carlo simulations—her debut TDS story!—became an immediate sensation among our readers.
Conversation-starters
We love articles that launch lively debates—or add an interesting angle to existing conversations. Here are three recent posts that excelled on that front.
- Is Decision Science Quietly Becoming the New Data Science?
If you’ve been wondering what decision scientists do and how this role differs from that of traditional data analysts, don’t miss Matt Chapman’s take (and the many spirited comments it generated). - Machine Learning Engineers — What Do They Actually Do?
Thanks to Stephanie Kirmer’s post on MLEs, we had the chance to see another excellent discussion unfold around the evolution of job titles and descriptions—and, in this case, how the latter sometimes reflect biases and tensions we should tackle head on. - Your Data’s (Finally) In The Cloud. Now, Stop Acting So On-Prem
The rapid evolution of data infrastructure in recent years has left many teams stuck somewhere on the cloud-to-on-premises spectrum. Fortunately, Barr Moses offers sharp insights on how to move on towards a more streamlined future.
Our latest cohort of new authors
Every month, we’re thrilled to see a fresh group of authors join TDS, each sharing their own unique voice, knowledge, and experience with our community. If you’re looking for new writers to explore and follow, just browse the work of our latest additions, including Jonathan Apple, Jarom Hulet, Sergey Vilov, David Rubio, Sydney Nye, Rüdiger Buchkremer, PhD, Michal Szudejko, Wanming Huang, John Lenehan, François Porcher, Tingsong Ou, Le Nguyen, Suyang Li, Ida Johnsson, PhD, Michael Segner, Radmila M., Chen Margalit, Pratik Aher, Gabriel L. Sena, Stan Pugsley, Caroline Arnold, Jeff Braun, Gianpi Colonna, Jaroslaw Drapala, Ahmad Albarqawi, Mateusz Praski, Julie Zhang, Joseph George Lewis, Thao Vu, Stefan Berkner, Ryan Shrott, Mary M, Eric Zhù, Stefan Suwelack, Maham Haroon, Jeff Chou, Berkan Zorlubas, Mariano Kamp, Douglas Blank, PhD, Gamze Zorlubas, Fatih Demirci, Jerry Qu, and Daniel Frees.
Thank you for supporting the work of our authors! If you enjoy the articles you read on TDS, consider becoming a Medium member — it unlocks our entire archive (and every other post on Medium, too).
Until the next Variable,
TDS Editors
