— Insight —
Great introduction to Data as a Service businesses by Auren Hoffman. Over the past 13 years, Auren has met with the CEOs of hundreds of data companies and has keen insights into how data companies work and where they're going. This is a long-read that explores strategies and opportunities. If you're short on time, start with the Twitter thread that introduces it >>
How hyping A.I. enriched investors, fooled the media, and confused the hell out of everyone.
— Profiles —
This is a great interview with Angela Bassa about innovation and the human side of data science.
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— Tools and Techniques —
You've probably heard that “king – man + woman = queen” but no one ever mentions that "gospel – God = jazz!" In this post, Grace Avery explores the funny side of Word2Vec.
MLflow recently released version 1.0, which means the API is stable and it's now generally available. If you're not familiar with it, MLflow is an open source platform that streamlines machine learning development, including tracking experiments, packaging code into reproducible runs, and sharing and deploying models. This announcement describes specific features and how to get started.
Tools for LaTeX
If you use LaTeX, check these out!
- Snip from Mathpix creates LaTeX code from a screenshot of an equation.
- This LaTeX add-in for PowerPoint by Jeremy Howard gives you an easy interface for adding editable LaTeX directly into Powerpoint.
Here's a SQL user interface for JupyterLab. Tested with SQLite, PostgreSQL, and MySQL databases.
Vettery specializes in tech roles and is completely free for job seekers. Interested? Submit your profile, and if accepted onto the platform, you can receive interview requests directly from top companies growing their data science teams.
— Resources —
If you're interested in sports analytics but not sure where to start, here's a great collection of articles and papers about the rapidly evolving space of ⚽️ analytics.
— Data Viz —
This step-by-step tutorial by Cédric Scherer shows how to create asthetic visualizations using ggplot2. This is well organized with lots of code snippets and screenshots.