"This service creates a Checkout UI for any valid 'nano_' or 'xrb_' address, for free. You can customize further with URL params or HTTP POST body data."
This is how I do it. I'm experimenting with using a TF-IDF
recommendation system to "categorize" everything so I can just think about what is interesting enough to not discard.
Then I can comeback to articles organized by keywords and take notes in obsidian when I'm digging deep.
I see two sides of this. There's information collection and knowledge keeping.
The information collection: When I'm learning new things and sorting by what is interesting I simple bookmark a lot of stuff. It could be a blog post, a research paper, a book recommendation etc. All this is raw information until I take the time to consume it and digest it. Here I use https://lxi.ai/ (disclaimer: I built this) to keep my bookmarks organized with a lil ML.
The knowledge keeping: While I consume/digest I take notes in obsidian. I like working in markdown and having everything stored locally is something that keeps me comfortable. The real key here is putting in the time and actually merging what I am learning with what I already have in my obsidian "second brain".
The graph is built with D3.js and some minor JS/CSS changes to create the hover effects.
The extensions are built with simple html/js/css - they're basically mini webpages with special permissions. For example, I use an activeTab api provided by the browser to read the page text when the user clicks a button.
Hey thanks for giving it a try! And yes, built it with python - specifically I'm using a modified version of gensim's TF-IDF model implementation. If you haven't heard of TF-IDF before give http://www.tfidf.com/ a read through.
It might be overkill to use tensorflow for TF-IDF, but go for it!
With lxi.ai, I use the top 10 most important keywords for the actual comparison along with some other tricks to make sure the model can scale. Might be worth a blog post or something.
Hello!, Everyone I know has a bookmark graveyard of bits of interesting information we wanted to come back to later but added into a general folder that ends up being a mess.
So I did what any good ML student would do and built a simple ML system (using TF-IDF vectors) that will recommend you similar bookmarks.
I use Obsidian.md as my second brain but needed a space to put the interesting links without spending the time to create a new note incorporate it into my organizational system. I think lxi.ai does a good job of being the middle ground for holding the interesting links for me to come back to when I really want to wrestle with the ideas. Hope some people like it too!
"This service creates a Checkout UI for any valid 'nano_' or 'xrb_' address, for free. You can customize further with URL params or HTTP POST body data."