Babak

@bkeyvani

Pythonista, Data Analyst, Web Developer, Machine Learning enthusiast / Data Scientist-to-be, Technologist, Geek, Aspiring Robotisist, & Hobbyist

teamluna.co
Vrijeme pridruživanja: siječanj 2009.
50 fotografija ili videozapisa Fotografije i videozapisi

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  1. Prikvačeni tweet
    7. stu 2018.

    A computer scientists' geeky scary office decoration

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  2. proslijedio/la je Tweet
    21. sij

    🚨New lecture series🚨 We've teamed up with to bring you the Deep Learning Lecture Series: 12 lectures covering a range of topics in Deep Learning - all led by DeepMind researchers, all free, and all open to everyone. Info & tickets:

    14 replies 480 proslijeđenih tweetova 1.330 korisnika označava da im se sviđa
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  3. proslijedio/la je Tweet
    5. sij

    Drifting in an autonomous vehicle. Uses rotation rate of the vehicle’s velocity vector to track the path, while yaw acceleration is used to stabilize sideslip. Could help autonomous vehicles in emergencies. Fun results.

    12 replies 161 proslijeđeni tweet 404 korisnika označavaju da im se sviđa
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  4. proslijedio/la je Tweet
    11. pro 2019.

    🐼🤹‍♂️ pandas trick #94: Want to save a *massive* amount of memory? Fix your data types: ➡️ 'int8' for small integers ➡️ 'category' for strings with few unique values ➡️ 'Sparse' if most values are 0 or NaN More info: by

    1 reply 36 proslijeđenih tweetova 172 korisnika označavaju da im se sviđa
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  5. proslijedio/la je Tweet
    8. pro 2019.

    This is amazing. I never thought my baby would have been used for such an important project! (Scanning of Rembrandt's Night Watch.)

    Odgovor korisnicima @erdmann @llanga @ProjectJupyter
    5. AsyncIO is great. It's been a joy to hook into 's async event loop so that I can send/receive messages to the robot, capture sensor data into a growing DataFrame, and run motion control programs in the background while having a free prompt for live analysis.
    11 replies 125 proslijeđenih tweetova 808 korisnika označava da im se sviđa
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  6. proslijedio/la je Tweet
    3. pro 2019.

    This year I wrote a book teaching Deep Learning - it's goal is to be the easiest intro possible In the book, each lesson builds a neural component *from scratch* in Each *from scratch* toy code example is in the Github below.

    26 replies 561 proslijeđeni tweet 2.287 korisnika označava da im se sviđa
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  7. proslijedio/la je Tweet
    29. stu 2019.

    I see a lot of "advanced Python" tutorials that talk about using map, filter, and reduce. Confession: I never use map, filter, or reduce. The first two are easily performed using list comprehensions or generator expressions. Common reductions are already there (sum, min, max).

    56 replies 161 proslijeđeni tweet 922 korisnika označavaju da im se sviđa
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  8. proslijedio/la je Tweet
    28. stu 2019.

    Fantastic free ebook on Linear Algebra written by my colleague Stephen Boyd at Stanford. Highly recommended. PDF: Page: Course:

    5 replies 127 proslijeđenih tweetova 443 korisnika označavaju da im se sviđa
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  9. proslijedio/la je Tweet
    26. stu 2019.

    Sure, you could use _ as a throw-away variable in a Python for-loop. Yeah, you could definitely do that... like everyone else. Or you could just do this: >>> a = [ (0, 'Hello'), (1, 'Satan') ] >>> for {}[()], x in a: ... print(x) ... Hello Satan >>> Be different.

    51 reply 140 proslijeđenih tweetova 633 korisnika označavaju da im se sviđa
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  10. proslijedio/la je Tweet
    26. stu 2019.

    The great robot apocalypse may not be so bad after all...

    12 replies 111 proslijeđenih tweetova 337 korisnika označava da im se sviđa
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  11. proslijedio/la je Tweet
    23. stu 2019.

    Another interesting use of 's walrus operator is to compute differences between successive values in a data stream. This is the inverse of accumulate(): >>> data = [10, 14, 34, 49, 70, 77] >>> prev = 0; [-prev + (prev := x) for x in data] [10, 4, 20, 15, 21, 7]

    27 replies 141 proslijeđeni tweet 644 korisnika označavaju da im se sviđa
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  12. proslijedio/la je Tweet
    21. stu 2019.

    "How to Scrape Yahoo Finance Data with Python"

    4 proslijeđena tweeta 5 korisnika označava da im se sviđa
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  13. proslijedio/la je Tweet
    18. stu 2019.

    outranks Java as the second most popular language among 40 million developers on , and contribution to open-source grows across the globe:

    15 proslijeđenih tweetova 47 korisnika označava da im se sviđa
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  14. proslijedio/la je Tweet
    15. stu 2019.

    🐼🤹‍♂️ pandas trick #87: Problem: You have time series data that you want to aggregate by day, but you're only interested in weekends. Solution: 1. resample by day ('D') 2. filter by day of week (5=Saturday, 6=Sunday) See example 👇

    42 proslijeđena tweeta 164 korisnika označavaju da im se sviđa
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  15. proslijedio/la je Tweet
    13. stu 2019.

    VS Code now supports editing and running Jupyter notebooks Honestly, I still did not switch from classical NB but better autocompletion and variable explorer seem tempting.

    21 proslijeđeni tweet 112 korisnika označava da im se sviđa
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  16. proslijedio/la je Tweet
    11. stu 2019.

    Easy way to get stock market prices (and others economic data): >>> from pandas_datareader import data as wb >>> ticker_name = '^GSPC' >>> ticker = wb.DataReader(ticker_name, start='2010-1-1', data_source='yahoo') More info:

    19 proslijeđenih tweetova 136 korisnika označava da im se sviđa
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  17. proslijedio/la je Tweet
    8. stu 2019.

    With the walrus operator while True: line = fp.readline() if not line: break do_something(line) can be written as: while line := fp.readline(): do_something(line) More examples:

    6 replies 68 proslijeđenih tweetova 287 korisnika označava da im se sviđa
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  18. proslijedio/la je Tweet
    6. stu 2019.

    🐼🤹‍♂️ pandas trick #81: Does your object column contain mixed data types? Use df.col.apply(type).value_counts() to check! See example 👇 Thanks to for inspiring this trick! Read more:

    32 proslijeđena tweeta 168 korisnika označava da im se sviđa
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  19. proslijedio/la je Tweet
    5. stu 2019.

    🐼🤹‍♂️ pandas trick #80: Want to select multiple slices of columns from a DataFrame? 1. Use df.loc to select & pd.concat to combine 2. Slice df.columns & select using brackets 3. Use np.r_ to combine slices & df.iloc to select See example 👇

    7 replies 50 proslijeđenih tweetova 217 korisnika označava da im se sviđa
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  20. proslijedio/la je Tweet
    4. stu 2019.

    🐼🤹‍♂️ pandas tricks is back! 🎉 Want to know the *count* of rows that match a condition? (condition).sum() Want to know the *percentage* of rows that match a condition? (condition).mean() See example 👇

    6 replies 81 proslijeđeni tweet 340 korisnika označava da im se sviđa
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  21. proslijedio/la je Tweet
    1. stu 2019.

    Playable sphere chess set. Mind expansion.

    18 proslijeđenih tweetova 95 korisnika označava da im se sviđa
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