Comes with free Data Science notes/code on various ML algorithms documented in Notion.
With Data Science being such an interdisciplinary field that has new tools almost every month, it is becoming more and more important to document your work and learning. Notion provides a beautiful workspace that is an engineer’s dream. You can map out/visualize project schedules, create to-do lists, build small websites with documentation, and build custom workspaces for whatever specific topic/project you are working on. As an active learner, yet unorganized individual I needed a source that was able to document small details and features that I could easily access later for future projects or problems I ran into. Notion is very simple to use and I won’t go into explaining how to build a workspace or to-do list as much of it is self-explanatory. However, I did want to provide a way I used Notion to enhance my understanding of various ML algorithms and also give a Notion link to my workspace for those trying to learn more about the implementation of these algorithms.
Sometimes for my Data Science projects, I wanted quick access to a template that had implementations of models that I could use as a building block for whatever project I was working on at the moment. Having a general source that contained theory and code for these algorithms in both the Python and R languages would save a lot of time and googling around. After downloading the Notion App, I used the “Create Page” feature to create a general directory with popular Machine Learning models.
I created sub pages within this directory for each model that I wanted to cover. Within these pages I then created another set of sub-pages that had the code implementations and pros/cons of each model. After this little bit of setup I had a directory that looked something like this.
If we look into one of the sub-pages you will notice that Notion has a handy code block feature.
Here you can pick the language that your code is in and embed it within this block.
This is just one of the many handy features Notion has and it lets your organize your notes quickly and in an aesthetic manner.
If you want to be able to access the Notion workspace with the code samples/theory click the following link. Note that some of these examples are incomplete and do not contain the code for both languages. The datasets are also not linked but are mostly on Kaggle and pretty easy to find. If you want a more in-depth set of examples for each of these models feel free to check out my other article or repository that comes with datasets and theory notes. I kept this article pretty short on purpose and just wanted it to serve as a gentle introduction to a tool that can greatly help your learning and even your time at work. Documentation is an essential aspect for any great developer or team and I feel that Notion helps makes this part of engineering seamless and clear.