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  1. Prikvačeni tweet

    In the context of local data tasks, map() fared better than map(). mpi4py fared worse at lower # of processes. I wonder if this will be true when number of local processes goes beyond 8.

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  2. Here's how we extended and analyzed storyboards to prevent 49 known from creeping into apps. Basic tooling that works with is available.

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  3. proslijedio/la je Tweet
    28. sij

    It's ! We're offering 30% off all our & books to help keep you . Use coupon code DATA2020 at checkout:

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  4. Fun read by . A quote for / Econ: I've tried everything. Diff eqns. Matrices. Metric spaces. So, why am I still not as precise as you, Physics? Physics: Econ, buddy, it's not how you model, it's what you model.

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  5. Actix-web component of project is gone. And, this seems to be due to community dynamics in . Honestly, we can do better as contributors and members of the community. by

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  6. Typing option (2) is consistent but the notation is not explicit. 'Union[Tuple[()], Tuple[int,...]]' with '...' meaning 1+ repetition is a more explicit and better alternative. Now, 'Tuple[int,...]' can be used to indicate n cannot be 0 in 'e = (1,3) * n'.

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  7. In , type hint for e in 'e = (1,3) * n' is 'Tuple[int,...]'. 1) If '...' means 1+ repetitions, then e takes on an inadmissable value '()' when n==0 😯 2) If '...' means 0+ repetitions, then '()' is common to all 'Tuple[X,...]' types 🤔

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  8. Python quiz: When n is an integer, what should be the type hint for e in "e = (1,3) * n"?

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  9. Got invited to use to collaborate on a project :) After using a combo of and for similar purpose (w/ mixed results), I'm hoping the experience with Basecamp will be better🤞

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  10. While the book covers a very interesting topic, the writing makes it a really slow read; even academic publications pale in terms of use of complex sentences and parenthetical references🤦‍♀️

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  11. Here's a pattern to provide different views of objects (e.g., read-only view of collection) in Python while hiding implementation details.

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  12. Interesting thread pointing out concerns to be aware of when migrating to cloud. Clearly no free lunch. Highlights challenges to improve cloud offerings.

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  13. Rather surprised that almost all of the I have read/skimmed do not discuss how to organize python projects, i.e., laying out folders and files in the file system.

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  14. "Grokking Deep Learning" by from is a great introductory book to learn about deep learning from ground up: concepts, their relevance, and how they are implemented and combined to realize deep learning 👍👍👍

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  15. "The main point of this chapter is to help prepare you for deep learning in the real world, where 10% (or less) of your time will be spent thinking up a new idea and 90% of your time will be spent figuring out how to get a framework to play nicely." 😂😂

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  16. While identifying unique values in a collection, using a list that is later converted into a set is better than using a set when the number of unique values is large.

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  17. Being disciplined in execution is a sure way to reduce the number of and extent of last mile problems. That said, building and practising such discipline takes quite a bit of practice and effort.

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  18. A short python script to organize files based their modification year and month. Great for organizing personal collections such as photos and videos.

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  19. proslijedio/la je Tweet
    20. pro 2019.

    Are you wondering if Kotlin can be used for data science? In a word, yes! Here’s a status update on the Kotlin tools, libraries, roadmap, and other useful resources for data science that you can already use today.

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  20. Fun fiction based on reality of software engineering.

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