Start Here - Entrance to the Garden

Welcome to my personal wiki.

This is a place where I collect notes, clippings and thoughts about what I read, be it papers or books. I tend to this wiki with love and care, and I am its main user, but I hope you will enjoy it too.

Unlike a blog, I don’t usually write my opinions in the wiki. Rather, I use this part of the site to organize what I learn and want to link to other ideas, maintaining evergreen notes in the way of Andy Matuschak and others.

You can browse this wiki by clicking any article that interests you, or use the search bar (tag-based search is implemented, but it also greps titles) to find topics you like. Recommended tags: paper, programming, book.

You may also find the Restaurant Guide to be of some interest.

Book Reviews

I have sometimes dreamt, at least, that when the Day of Judgment dawns and the great conquerors and lawyers and statesmen come to receive their rewards — their crowns, their laurels, their names carved indelibly upon imperishable marble — the Almighty will turn to Peter and will say, not without a certain envy when He sees us coming with our books under our arms, “Look, these need no reward. We have nothing to give them here. They have loved reading.”
- Virginia Woolf

I save every quote I found especially interesting in each book on a separate page of this wiki. I also usually write a summary of the book and the impressions it left me.

These are the books where the notes were abundant enough to be interesting. See also the books category page for more.

Online Courses

These notes encompass multiples sources, but usually form around a MOOC (Massive Open Online Course) and then get updates as I go through the recommended reading.

Computer Science and Deep Learning




If I read a paper, find it interesting, and think I will want to consider it again in the future (especially if I plan on reading related papers later), I will write a summary and save the most important discoveries or explanations. These are the papers I’ve read so far (mostly in the Machine Learning/Deep Learning space). [Under tag: paper ]

If you have anything to say about one of the articles, you find an error in one of them or just like something you read and want to chat, don’t be afraid to tweet at me or send me an email. I will reply kindly, and be happy if you reach out! I also answer DMs on Reddit.

Size of the Site

In case someone may find it interesting, as we digital garden / personal knowledge management types like comparing sizes, here’s how big the whole site is. I will update this every few months, as it doesn’t grow that quickly anyways. Last updated: March 6th, 2023.

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    word count: 

    Markdown files: 
        2408 total
    word count: 
        28002 total

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15 Jun 2022 - importance: 11