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Hi there 👋

I value:

  • learning/planning
  • acting -- and subsequently learning by acting
  • repeating this virtuous cycle
  • helping others learn

My view: Learning best occurs when the greatest number of associations can be made in your brain -- i.e. by doing something, you experience the most relevant inputs, and these are the associations that provide "hooks" for learning. So, I aim to have a bias towards action rather than overthinking -- unless the action is thinking :)

Here is my framework: My Learn-->Plan-->Act Framework)

Here is another framework that I got from Alex Hormozi: First do more --> do better --> then do new. New and "shiny" is exciting and tempting, but this framework helps me remember to not change what I am doing unless I have first done more of it, doing what I am doing better, and if I am still not succeeding, then switch and do new. First do more --> do better --> then do new

Infoverse AI

My passion project is called (Infoverse AI). Currently, the web application enables users to search Wikipedia and visualize topics as a graph network as well as view Wikipedia articles in a split-pane view. The goal is to provide the user with a top-down view of a topic, with the capactity to interact with information in an increasingly detailed fashion -- as the user desires. If you hover over a graph node, a brief description of the node topic is shown, and if a Wikipedia article is available on the topic, you can select the Wikipedia icon to open the split-pane view to read the article.

Current Tech Stack

Languages

  • JavaScript
  • TypeScript
  • Python

Frameworks

  • React
  • NextJS
  • Tailwind CSS
  • D3.js

Hosting

  • Vercel

Contact Me

Jon Sundin's Projects

algorithms icon algorithms

Solved algorithms and data structures problems in many languages

anytype-ts icon anytype-ts

Official Anytype client for MacOS, Linux, and Windows

arbor icon arbor

a graph visualization library using web workers and jQuery

arrows icon arrows

JavaScript library for drawing diagrams of small graphs, using D3 to generate SVG. Useful for explaining Neo4j graph modelling concepts in presentations and blogs.

awesome-cv icon awesome-cv

:page_facing_up: Awesome CV is LaTeX template for your outstanding job application

causalnex icon causalnex

A Python library that helps data scientists to infer causation rather than observing correlation.

computer-science-flash-cards icon computer-science-flash-cards

Mini website for testing both general CS knowledge and enforce coding practice and common algorithm/data structure memorization.

cramming icon cramming

Cramming the training of a (BERT-type) language model into limited compute.

cytoscape.js icon cytoscape.js

Graph theory (network) library for visualisation and analysis

d3 icon d3

Bring data to life with SVG, Canvas and HTML. :bar_chart::chart_with_upwards_trend::tada:

developer-roadmap icon developer-roadmap

Interactive roadmaps, guides and other educational content to help developers grow in their careers.

dowhy icon dowhy

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

dsa icon dsa

Data Structure and Algorithm (DSA) contributions

excalidraw icon excalidraw

Virtual whiteboard for sketching hand-drawn like diagrams

fltr icon fltr

foreign language text reader

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