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Based on our record, HackerNews Readings seems to be more popular. It has been mentiond 4 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Wouldn't a traditional spacy NER pipeline be way more efficient for this (you could even use GPT to label the training data)? Edit: Someone did this at scale in the past https://hacker-recommended-books.vercel.app/category/0/all-time/page/0/0. - Source: Hacker News / 8 months ago
I found this on HN [0], and began reading through it, tried many books, read around 20 of them. The experience has been great, and learned many new things. Some books have expanded my mind. If you are into books, I highly recommend searching HN with the simple keyword "books", and filter using "Ask HN" tags [1], or simply by "books". This is how I read almost all of my English books from (I am trilingual and can... - Source: Hacker News / 8 months ago
I am looking forward to reading the whole thread, but while people are at it, you can check this out: https://hacker-recommended-books.vercel.app/category/0/all-time/page/0/0 You could also find nice websites and collections if you Google "Hacker News books". Hacker News has become one of the most impactful places in determining what to read. I have read at least 10 books as suggested in HN comments by others... - Source: Hacker News / over 2 years ago
Show HN: 40k HN comments mentioning books, extracted using deep learning\ (250 comments). Source: over 2 years ago
Hacker News Search - a faster hnsearch
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