Cool Stuff

  • Data Science

    • Software

      • Languages

        • Python. Most popular language for data science in industry. Also well-suited to application building.

        • R. Most popular language among statisticians. Excellent focus on user experience, and lots of amazing tooling.

        • Julia. A beautifully designed, fast, and increasingly popular language for data science and other scientific computing applications. My personal favorite.

      • Packages

        • Plotly. Beautiful, easy-to-make graphs for the web (both 2D and 3D). Very well integrated with Python, R, and Julia.

        • Tidyverse. An opinionated but powerful collection of packages for doing data science in R.

        • Esquisse. An R package for creating data visualizations quickly and beautifully, without code.

        • Spark. Distributed computing framework, commonly used in industry.

      • Applications

        • Jupyter. Very popular notebook computing environment which supports many languages, including Julia, Python, and R.

        • Pluto. Julia-specific alternative to Jupyter which is reactive (changing anything causes everything downstream of it to change too).

        • ObservableHQ. Reactive notebooks specifically for Javascript.

        • RStudio. Premier development environment for R. Can also be used for both Python and Julia.

        • Superset. Open source data visualization dashboards.

      • Miscellaneous

        • RAWGraphs (rawgraphs.io) Kind of like Esquisse (or Superset), but it works as a web app that you can paste your data into as a CSV. Gives you a ton of cool visualizations and ways to map the data.

    • Websites

      • Applications

        • CoCalc. Cloud environment with excellent collaboration tools which supports practically every piece of open source scientific computing software.

        • Colab. A Google-managed cloud Jupyter environment; Python-only and with slightly hackish support for collaboration, but it does include free GPU, which is important for deep learning and some other applications.

        • NextJournal. Another free-GPU cloud Jupyter service.

      • Books

        • Introduction to Data Science in R. Superb online book written by Rafael Irizarry at Harvard.

      • Community

        • Kaggle. Datasets, problems, and contests.

      • Visualizations

        • Seeing Theory. Introduction to probability and statistics with some great visualizations. Based on D3.

        • Permutation Test. Very nice scrollytelling exposition.

  • Content creation tools and utilities

    • Prismia. Create and deploy interactive lessons.

    • Desmos. A mathlet creation environment for everyone.

    • math3d.org. Desmos, but in 3D. Really beautiful.

    • JSXGraph. Create reactive mathlets (with code). What Prismia uses for its 2D mathlet system.

    • Ipe. Desktop application for making precise 2D mathematical figures quickly (using a graphical user interface).

    • TinyTeX. An easy-to-use distribution of LaTeX that does not take up a ton of hard drive space.

    • MathPix. Snapshot math expressions or tables on your screen and convert them automatically to LaTeX (using optical character recognition).

    • TextSniper. Like MathPix, but with plain text. For macOS.

    • Keyboard Maestro. Automate tasks at the operating system level (e.g., scroll down 60 pixels and click, then repeat 100 times). Hopefully you don't need it often, but it's a lifesaver when you do.

    • Copier. Templating system for quickly creating new files or projects on your computer (a Python package). Especially useful for software projects with boilerplate, stock letters, etc.

    • ungit. A visual approach to version control. Solves a lot of Git's UX problems.

  • Web development

    • React. One of the most popular Javascript frameworks for creating web applications.

    • Svelte. A front-end framework that's simple, really fast, and genuinely reactive.

    • Visual Studio Code. The development environment that all the cool kids are using these days.

    • Firebase. An easy way to create a low-cost, scalable web application. Hosting, database, and cloud functions are all integrated and well documented.

    • AG Grid. Possibly the best open source data table package for the web. Highly recommended over plain HTML for large tables.

  • Learning

    • Websites

      • Art of Problem Solving. Premier math learning community for middle school and high school.

      • Mathigon. Most polished, beautiful math lessons on the internet.

      • Data Gymnasia. Data science content built on Mathigon technology.

      • 3Blue1Brown. The best math videos on YouTube. Beautiful visualizations, original exposition, and excellent storytelling.

      • Distill.pub. Visually stunning interactive articles on data science topics.

    • Books

      • Concrete Mathematics by Knuth, Graham, and Patashnik. Original, expertly crafted book on a variety of discrete math topics.

      • Probability with Martingales by David Williams. Succinct probability textbook from the University of Cambridge (the one I learned basic probability from).

      • Linear Algebra Done Right by Sheldon Axler. An expository masterpiece with an original and elegant take on basic linear algebra.

      • Visual Complex Analysis by Tristan Needham. The title says it all.

  • Personal

    • Transportation

      • Bike Friday. Really cool folding bicycles (better ride).

      • Brompton. Really cool folding bicycles (more compact).

    • Food

      • Taza Chocolate. Amazing chocolate made locally in Somerville. Unique, slightly gritty texture (and dairy free).

    • Entertainment

      • xckd. Premier nerd comic on the web.

      • Quora. Social media site built around the question-and-answer concept. Lots of excellent writers and a good algorithm for surfacing quality content.

      • Meetup.com. Find folks in your area with common interests.

      • Pocket. Browser extension and app for stashing articles you find and want to read later.