On HackerNews someone gave a plausible explanation for the timestamps: They are regenerated when you download the PDF with the result.
This explains the inconsistencies in the timestamps – but not in the confirmation codes – because they remain the same.
And the inconsistencies also exists in them. The confirmation codes are ascending, so the result from the 16th should have a lower number than the one from 22nd. However, it is the other way around.
Best rated related books across r/askprogramming, r/programming, r/cscareerquestions, r/learnprogramming.
This is an updated list, calculated on data since 2011 up to September 2019 and based on a number of upvotes, mentions, and Reddit golds.
The selection contains Top 55 best books including their top comment.
Thats super cool.
We built a simmilar simple app on a Hackathon.
We are getting 90% Accuracy nowadays.
We opensourced it at https://github.com/kuboris/smartoscope
We should add an App for download as soon as our Android developer fixes some minor bugs.
The plan is to make it open to use any model so people can train and provide their own.
Any advice ? :)
I'm in the process of adding Goodreads and other book websites to get better suggestions.(Using Amazon API is limiting on scale)
As for your question: I've been researching python natural language processing to get probable named entities and check them against Amazon API. I suggest https://spacy.io that has reasonable named entities extraction. However doing it at a scale might produce lot of books that are named as a common phrases.
I just want to mention that I loved the idea of BlueOcean at the begining. It looks sleak an works well with pipeline. However, for us it's unusable in production setting.
I know that it's still in beta, but as one example it doesn't support parameters. When user starts a job through BlueOcean it will fail.(Officialy they don't plan to implement it any time soon as I found out) That means It stays disabled in our jenkins. PS: For now its just a presentation tool for management :)