— In the News —
With algorithms in hand, scientists are looking to make elections in the United States more representative. Easy, right?...
AI is presenting enormous opportunities for startups - but where? This deep dive by Bradford Cross explores the AI startup landscape and offers practical advice for selecting opportunities. Bradford is a founding partner of DCVC (Data Collective), the world's leading machine learning and big data venture capital fund. His insights are informed and worthwhile.
J.P. Morgan recently released a 280 page report titled, Big Data and AI Strategies. This article explores the key points, which all indicate fundamental shifts in how data is used and the skills that are quickly becoming required in data-intensive industries.
— Sponsored Link —
Mode is a SQL editor, Python notebook, and visualization builder all rolled into one. Explore data with SQL and pass results instantly into a Python notebook for further exploration and visualization. Pick and choose output cells to present to others, or send the whole notebook—you can even share with people who don't have a Python environment set up.
— Tools and Techniques —
Readily available analytics tools make it easy to analyze data and perform complex statistical tests. That also makes it easy to misunderstand some of the subtleties within a dataset and to draw wildly incorrect conclusions. This post explores some common statistical fallacies and shows how they can lead to results that are counterintuitive and, in many cases, simply wrong.
R is super useful but it's tricky to use R in production environments. This post by the team at StitchFix walks through some of the problems that they've encountered and offers specific packages and tips to make life easier.
Here's an overview of the most popular anomaly detection algorithms for time series data. Includes pros and cons for each and links to useful libraries and resources.
This is Part 2 of a multi-part tutorial that demonstrates how to approach common business questions. In this part, Shirin Glander introduces the timekit package, which enables time series forecasting with machine learning.
— Data Viz —
This comprehensive tutorial is a fantastic starting point for planning graph visualizations using R. Includes use cases for various graph types, lots of diagrams, interactive examples, code snippets, tips, etc, etc.