See that picture of a person? AI did that, and that person doesn’t exist.

Different types of data people: Machine Learning, Statistics, and Analytics

A brief rundown of methods/packages/ideas to generate synthetic data for self-driven data science projects and deep diving into machine learning methods.

Quickly becoming a regular check-in for ideas and methods for Data Science.

Chapter 6 of a series from Humanlytics complete with code examples and more.

If you are manipulating large datasets in excel and are tired of dealing with long wait times, check this out.

Killer environment to help you learn and test python, plus much more.

Creator of D3 and Observable. Former data scientist at the New York Times.

A roundabout tutorial to a SQL tool called the Data Build Tool (dbt).

You know those cool New York Times charts you see from time to time? They probably use this.

A collaborative platform for data science built by the founder of D3.

A poorly structured collection of relationship files helpful with matching back zip codes, counties, etc, to congressional disctricts.

Finished it. Pretty decent. Took notes.

Going to get to this after Codecademy.

Kind of want to check this out, but when I first looked, the docs were limited.

I honestly have no idea what this does yet, but I want to look into it. Looks like some kind of workflow management tool.

Supercharge your data pipeline using the Coding Is For Losers stack. From data collection to visualization, plus some extra tactics.

Another ETL with the option to create your own connectors; think of an ETL as Zapier or IFTTT but for data.

Just getting started exploring this one, but I can already see a world of possibilities.

This is LinkedIn’s Data on the Work Force. It includes where workers are leaving and where workers are going.

Link to the U.S. Bureau of Labor Statistics data section.

The Founder of Seer Interactive’s slideshare. Includes 50+ decks most recently on data visualization.

U.S. Census data in directory structure.

Directory of IRS individual income tax data by zip code and year.

If you’re new to reporting, check out this article and short video for some ideas to kickstart your dashboards.

I check this subreddit periodically for new ideas on data visualization. You’ll find the work of some very talented data scientists here.

Step by step guide to a 100,000+ headline analysis of clickbait using Apache Spark and Word2vec by Max Woolf.

A huge, community driven library of datasets with connectors to Power BI and Google Data Studio.

I need to do a better job keeping up with this one. Anyone dealing with Places or Planning should check this out.

Zillow’s collection of data on everything from zestimates to home sale counts and prices.

Fantastic data blog on cities.