[lucasschm]

You are correct, but HyperLogLog has many buckets counting the longest run of zeros in order to avoid the problem of outliers. I recently studied these probabilistic algorithms and did a notebook with code and plots to show their performance: https://github.com/lucasschmidtc/Probabilistic-Algorithms/bl...

[snowcrshd]

Thanks for sharing that!

Just skimmed through it and seems pretty interesting. I'll read it more in depth later.

[lucasschm]

No problem. If there are mistakes or a segment is not clear, let me know

[meetapoorvgupta]

Thanks for the write up, Lucas. It was very intuitive and I learnt a lot.

I noticed that you used 5000 buckets to store the frequency of 7000 non-unique words in the section on 'Counting Bloom Filters'. How is that better than using 7000 buckets and a uniformly distributed hash function, which would maintain frequencies perfectly? We would be using fewer buckets by an order of magnitude in a real-world implementation to save memory.

[lucasschm]

Yeah, I should have given more thought to that number. Updated the example for N=300. Thanks

[anhldbk]

Thanks for sharing guy! Interesting repo.