ISSUE 352 ·   September 7, 2021

Trends

How Midsize Companies Can Compete in AI

Startups and multi-billion dollar giants are well-positioned to leverage AI's capabilities but mid-sized companies are being left behind. Here's how joint AI ventures can help them catch up.
Harvard Business Review

Sponsored Link

Understanding Bias in AI: What is it, how to identify it, and how to mitigate it.

It’s no secret...bias in AI is a problem. The more powerful AI capacity becomes, the more important it becomes to ensure that we are producing tools that make life better for more people, not simply scaling and perpetuating forms of error. That’s why we’ve created a guide to understanding and addressing possible sources of bias for your AI/ML project.

Tutorials, Projects & Opinions

Twelve Software Design Tips for Data Scientists

You may not need to write large programs that scale but the tips outlined here will help make sure that even small scripts are clear, easy to maintain, and designed to evolve. This is a super useful post, especially for non-engineers. For a streamlined version, see the slides.
Greg Wilson

A Gentle Introduction to Graph Neural Networks

Awesome introduction to graph neural networks, starting with the basics of graphs and what makes graph data different from other types of data. With lots of visualizations along the way, this post gradually explains and builds out a GNN from a bare-bones implementation to a state-of-the-art model. There's a lot to learn and play with here. 
Distill | Google Research

Multiplying Matrices Without Multiplying

This paper introduces a learning-based algorithm for multiplying matrices that greatly outperforms existing methods. It's important because matrix multiplication is one of the most fundamental operations in machine learning and this new approach looks FAST!
arXiv | Davis Blalock, John Guttag

Decision Making at Netflix

This introduction is the first in a multi-part series on how Netflix uses A/B testing to make decisions. This post lays the groundwork. Upcoming posts will cover statistical concepts, infrastructure to support and scale tests, the role of experimentation, and the importance of culture.
Netflix Tech Blog

TLDR Newsletter - Byte sized news for busy techies

TLDR is a daily newsletter with links and TLDRs of the most interesting stories in tech 📱, science 🚀, and coding 💻! Sign up for free today.
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Resources

Recommenders

Nice collection of examples, best practices and Python utilities for building and evaluating recommendation systems.
GitHub | Microsoft

Python Packages

Python packages are a key part of the language that enable you to create reusable, organized, and shareable code. This open-source book shows how to build efficient workflows for creating Python packages, including package organization, testing, versioning, CI/CD, and more!
py-pkgs | Tomas Beuzen and Tiffany Timbers

Data Visualization

Analyzing Geospatial Data in Python

Nice introduction to working with geospatial data using Python. Covers data types, common pitfalls, map projections, and how to work with and visualize data using the GeoPandas and Shapely libraries. 
LearnDataSci | Ioannis Prapas

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