Make Python code 1000x Faster with Numba

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  • เผยแพร่เมื่อ 19 มิ.ย. 2024
  • In this video I introduce Numba which can make your python code 1000x faster. Numba is a just in time compiler for a subset of Python and Numpy. The first half of the video is dedicated to a basic intro and to highlighting a number of very common mistakes people make when using Numba. The remaining video show how to use Numba in a real world-ish simulation problem and shows the code running 1000x faster with Numba in both single and multithreaded cases, and concludes with a "reading list" for learning more about Numba.
    Twitter: / safijari
    Find the notebook here: gist.github.com/safijari/fa4e...
    MY OTHER VIDOES:
    ○ A.I. Learns to play Snake • Neural Network Learns ...
    ○ 5 Common Python Mistakes: • 5 Things You're Doing ...
    ○ 5 Amazing Python Libraries: • Five Amazing Python Li...
    ○ Making Python fast: • Can VSCode be a reason...
    ○ Learning programming language Julia: • How to learn Julia, a ...
    Deeper topics to discover here
    numba.pydata.org/numba-doc/de...
    Supported python and numpy features
    numba.pydata.org/numba-doc/de...
    numba.pydata.org/numba-doc/de...
    Important differences from python numba.pydata.org/numba-doc/de...
    Defining types to compile at definition time: numba.pydata.org/numba-doc/lat...
    Function factories numba.pydata.org/numba-doc/de...
    Experimental version of jitted classes numba.pydata.org/numba-doc/de...
    Debugging numba.pydata.org/numba-doc/de...
    Dealing with types numba.pydata.org/numba-doc/de...
    Ahead of time compilation for deployment numba.pydata.org/numba-doc/de...
    Using approximate fastmath numba.pydata.org/numba-doc/de...
    Deeper control of threading via tbb and/or omp numba.pydata.org/numba-doc/de...
    Easily put your computation on a GPU!
    numba.pydata.org/numba-doc/de...
    numba.pydata.org/numba-doc/de...
    F.A.Qs numba.pydata.org/numba-doc/de...
    #numba #programming #python

ความคิดเห็น • 684

  • @gdsvsrv
    @gdsvsrv 3 ปีที่แล้ว +504

    finally, my print("hello world") can run at the speed of light!

    • @felicytatomaszewska2934
      @felicytatomaszewska2934 2 ปีที่แล้ว +1

      That's not true

    • @MartinoxxHD
      @MartinoxxHD 2 ปีที่แล้ว +11

      @@felicytatomaszewska2934 no way

    • @dv_interval42
      @dv_interval42 2 ปีที่แล้ว +15

      This meme is much closer to the truth than people would think.

    • @hanchen2355
      @hanchen2355 2 ปีที่แล้ว

      You can’t because it’s IO

    • @aryanmn1569
      @aryanmn1569 2 ปีที่แล้ว

      @@dv_interval42 how?

  • @MichaelKudlatheInterested
    @MichaelKudlatheInterested 3 ปีที่แล้ว +596

    Amazing, amazing video. As a PhD student, I'm sure you've saved me much more than 8 hrs of compute.

    • @JackofSome
      @JackofSome  3 ปีที่แล้ว +297

      I expect a co-author ship on all your papers now 👀

    • @sorry4all
      @sorry4all 3 ปีที่แล้ว +7

      Lol

    • @senwang1982
      @senwang1982 3 ปีที่แล้ว +11

      @@JackofSome fair enough😂

    • @alexp6013
      @alexp6013 3 ปีที่แล้ว +6

      I've once had code run for 48h, so I fully believe that it could be true

    • @username42
      @username42 3 ปีที่แล้ว +16

      @@JackofSome i think he will thank you in the acknowledgement part in his thesis for sure :)

  • @tronali5703
    @tronali5703 4 ปีที่แล้ว +63

    One thing to note is that Numba really optimizes nested loops. If you say have to call a function a 100 or million times, better to have an outerloop instead that iterates within the function. With parallel turned on, you can see a 1000x increase.

    • @JackofSome
      @JackofSome  4 ปีที่แล้ว +9

      This actually makes a lot of sense. Thanks for the comment!

    • @chriskeo392
      @chriskeo392 2 ปีที่แล้ว +2

      This is crazy! Awesome

    • @AlexanderHyll
      @AlexanderHyll ปีที่แล้ว +3

      Its one of the only ways to run the notoriously slow nested loops in Python (whenever it can’t be vectorized). We had a simulation to run that went from 81 days pure python to 2h (~1000x).

  • @klioseth4336
    @klioseth4336 3 ปีที่แล้ว +45

    Seriously this is brilliant.
    By applying this to the 3 main functions of a 1500 lines project I went from a 24 minutes runtime to about 20 seconds. that's 70X faster for a day's work (it'd be faster now that I learned the more complicated details). The C++ equivalent of the code does it in about 15 seconds.

  • @ger15100
    @ger15100 3 ปีที่แล้ว +31

    Numba really is great. Here is my first experience with it: I have some code that I estimated would take up to half a year to run. With some minor changes to the code for compatibility with Numba, the run time for the same conditions was up to 1.5 hours. This was a game-changer for me as I needed to run this script many times.
    One of my colleagues also implemented it into his machine learning code and managed to obtain some significant speed bumps.

  • @joshuatyler4657
    @joshuatyler4657 2 ปีที่แล้ว +16

    I implemented it in my code, and it took around an hour worth of computation and put it down to 30 seconds. Amazing stuff.

    • @JackofSome
      @JackofSome  2 ปีที่แล้ว +2

      Nice nice!

    • @joshuatyler4657
      @joshuatyler4657 2 ปีที่แล้ว +4

      @@JackofSome One funny thing that I found is that you can’t create numpy.linespace or numpy.arrange arrays with anything besides integers. I had to create an integer array, then divide it by 2 to make it a float32, and then populate it with a for loop to get the actual array I wanted. Also, numpy.zero arrays have to be initialized outside of the function and passed as an argument instead of being initialized in the array. But the extra work is worth the speed up.

  • @id104335409
    @id104335409 3 ปีที่แล้ว +122

    I nod my head with approving noises as if I understand what is going on.

  • @saurabhpareek3310
    @saurabhpareek3310 3 ปีที่แล้ว +17

    I am in tears to see my code run so fast, thank you so much for this video

  • @irok1
    @irok1 3 ปีที่แล้ว +357

    Finally, this is what Python has needed

    • @raycao88124
      @raycao88124 3 ปีที่แล้ว +26

      Just use C🤣

    • @JackofSome
      @JackofSome  3 ปีที่แล้ว +46

      cPython is already "just use C" so not quite

    • @tsunekakou1275
      @tsunekakou1275 3 ปีที่แล้ว +30

      python doesn't need to be faster, it designed to be simple not efficient. there are plenty other programming languages that designed to be efficient like C, C++ that has proved themself. sure they are hard to learn but trying to get python faster is just like reinvented the wheel, learning C++ from scratch in my opinion is much more beneficial in long term than trying to make python faster because essentially you are learning the same things but you won't get far with python.

    • @tando6266
      @tando6266 3 ปีที่แล้ว +42

      @@tsunekakou1275 Couldn't disagree more, for a lot of science we are paid to do things, not write c++ libraries to do things. As much as I like C++ it is woefully inadequate for a research setting with deadlines.

    • @tsunekakou1275
      @tsunekakou1275 3 ปีที่แล้ว

      @@tando6266 which points?

  • @AnthonyThomas_Ant
    @AnthonyThomas_Ant 3 ปีที่แล้ว +1

    Liked and subscribed. The length and pace of the video were spot on, especially as you’ve shared the notebook.

  • @peterbonnema8913
    @peterbonnema8913 3 ปีที่แล้ว +2

    Both Numba and this video are amazing. The video was really really clear and concise. I'm definitely gonna remember Numba for future projects.

  • @valente.victor
    @valente.victor 3 ปีที่แล้ว +67

    This is one of the best programming-related video tutorials I've ever seen. No-nonsense style, very direct and still computationally rigorous. Awesome stuff!

  • @jafarjuneidi7585
    @jafarjuneidi7585 3 ปีที่แล้ว +9

    I already had a background in Numba but I thoroughly enjoyed this video and learned some useful details as well.
    I'd be glad to see some more python related videos from you

  • @kaandonbekci6414
    @kaandonbekci6414 3 ปีที่แล้ว +65

    Similar to other commenters, I have to say this is one of the best TH-cam tutorials on writing fast Python code. Great buildup to the mic drop moment, amazing progression. Jack, I hope you make it big in the CS-tutorials TH-cam space and have a great day.

    • @JackofSome
      @JackofSome  3 ปีที่แล้ว +9

      Thanks for the kind words. Videos have been recommended a lot lately so fingers crossed.

  • @preyasurakshit3405
    @preyasurakshit3405 3 ปีที่แล้ว +8

    I cannot thank you enough for this video. I made a simulation of Gray Scott's Reaction diffusion in python, but it was painstakingly slow. After using numba, it now runs quite fast. Earlier it took nearly about 1 hour to render just 100 frames at a mere 400x400 resolution, now it renders 100 frames in 45 seconds, in 1280x720 resolution. Thank you very much for this video.

    • @JackofSome
      @JackofSome  3 ปีที่แล้ว +1

      That's amazing to hear! Glad it could be helpful. Would love to see the result.

    • @JackofSome
      @JackofSome  2 ปีที่แล้ว

      If you're just trying to do convolutions then you might want to look into numba's own way for doing them. I forget what it's called but it's optimized specifically for the convolution operator

  • @graemeford1333
    @graemeford1333 3 ปีที่แล้ว +7

    Ah yay. Thanks for this. I must say Numba is very impressive. What I am most interested in though is applying it to a research setting which you helped a lot with as well! I am just happy that it was designed for scientific applications as well!

  • @muhammadanas1201
    @muhammadanas1201 2 ปีที่แล้ว +2

    I had to submit a project in 2 days (that I had months to do but waited until the last minute) and in one piece of code, I needed to clean data of 6 million tweets. Regular python code showed runtime of 400+ hours (I used tqdm library for it). I got cold feet thinking I’m going to miss the deadline, but finally got the idea to search for ways to make the code faster. Found this library out on the internet and using it, I was able to run that piece of code in JUST 10 MINUTES. This library saved my project that day 👌.

    • @JackofSome
      @JackofSome  2 ปีที่แล้ว +2

      Numba: enabling procrastinators since 2012 😂

  • @drepi57
    @drepi57 3 ปีที่แล้ว +2

    Jack!!! Congrats for this fast, clear and insightful video. This is a game changer for me (I'm a Fortran 77...20** programmer now starting with python). Live long and prosper \\//

  • @TimmyTam
    @TimmyTam 3 ปีที่แล้ว +3

    I really thought the title was clickbait. It wasn't. This is honestly amazing, thanks for showing us this :D

  • @boyuanchen4997
    @boyuanchen4997 2 ปีที่แล้ว

    Simple, effective, to-the-point! Encountering a topic modeling problem that requires a lot of steps of training, I was about to try cython which would have taken a huge amount of time. Numba turned out to be ENORMOUSLY SIMPLER and equally effective. Many thanks to numba developers and Jack!!

  • @sirosala
    @sirosala ปีที่แล้ว +2

    Excellent video, in one day I implemented 80% of the code and strategies you explain. Very good ! Greetings from Rosario - Argentina.

  • @jackrdye
    @jackrdye 3 ปีที่แล้ว

    Why didn't I find this sooner. I am still so glad I found it will 100% use this in the future. Literally had a situation identical to ur example a month ago needed to simulate over 160,000 situations. Was taking 11+ hours to run. I assumed there were better ways but I haven't had a lot of experience. Thanks for this very clear explanation

  • @mpilosov
    @mpilosov 2 ปีที่แล้ว +3

    This was wonderfully clear and helpful! Thank you!
    My PhD involved running a lot of these forward problems under uncertainty, Lost much time trying to parallelize physics simulations and fighting with the GIL. Sometimes it is just worth waiting.

  • @syoudipta
    @syoudipta 9 หลายเดือนก่อน +2

    After being skeptical about this library for a while, I've gotten used to it. I've watched many tutorials and read many articles and documentation. After weeks of determination to learn this technique properly,...
    I have become, comfortably Numba. 🤟

  • @jmnunezd1231
    @jmnunezd1231 4 ปีที่แล้ว +238

    One of the most awesome Python tutorials I have seen. The narratives, the examples and the way you explain it is just awesome, 5 starts to you man! keep on doing it!

  • @dinoscheidt
    @dinoscheidt 2 ปีที่แล้ว

    Awesome video. Simply forwarded this to two of my junior devs and they completely got it now. THANK YOU!

  • @nitsanbh
    @nitsanbh 2 ปีที่แล้ว

    This is one of the best intro/tutor videos I’ve ever watched on any subject

  • @raccoonteachesyou
    @raccoonteachesyou 3 ปีที่แล้ว +3

    Damn, I love your Python videos ! Very interresting, you talk about stuff other don't. Thx man !

  • @lordtejas9659
    @lordtejas9659 3 ปีที่แล้ว +2

    You deserve my like. Nice work sir. Now I can show to my friends how a optimizated and we'll written code looks like. Numba.

  • @gabrielcesar568
    @gabrielcesar568 3 ปีที่แล้ว +9

    Grad students from around the world are thankfull for this video.

  • @jakubkahoun8383
    @jakubkahoun8383 ปีที่แล้ว

    This is the best Numba video, short , good examples etc.

  • @user-bf4kb5hm4n
    @user-bf4kb5hm4n 3 ปีที่แล้ว +3

    Thanks for your introduction! This really helps me. I have been working with Numpy but it is too time-consuming. Working with Numba is really fantastic, my Python module runs more than 1000x faster than the original one.

    • @Xaminn
      @Xaminn 3 ปีที่แล้ว

      Recursive Fibonacci will truly get ya.

  • @vishawashkumar5159
    @vishawashkumar5159 3 ปีที่แล้ว +2

    This needs much more views.. This is a revolution..

  • @ViralKiller
    @ViralKiller 2 ปีที่แล้ว

    4:06, so why can't you copy and paste this cached code into a new function, so it executes fast even on first run?

  • @eddantes_
    @eddantes_ 3 ปีที่แล้ว

    Great video. The fact that you are sharing the jup notebook is amazing. Thanks a lot. Please consider making a follow up video with more complex applications of numba. For example, integrations!

  • @dmgeo
    @dmgeo 3 ปีที่แล้ว

    Thank you for your video. I work with satellite image processing and we are used to spend hours waiting for a particular processing task to finish... I for sure will be trying to use Numba

  • @andylib
    @andylib 3 ปีที่แล้ว +6

    This was awesome !! Sooo interesting, straight up going into this

  • @Blooddarkstar
    @Blooddarkstar 3 ปีที่แล้ว

    Very well explained and saved me from some mistakes. You deserve way more subscribers!

  • @MrRyanroberson1
    @MrRyanroberson1 3 ปีที่แล้ว +1

    this is absolutely perfect because i just found this while running a really oddly intensive random number process (something like one million terms per second? i need billions) and numba sped it up by a factor of 100 halfway through the video, and with njit it didn't actually speed up any further, it just got a more consistent time (randomly jit is 10% faster or slower depending i guess on the random values

  • @MisterFresh022
    @MisterFresh022 2 ปีที่แล้ว +10

    What an amazing video. I'm a student in Computer Science and we just did a week ago an introduction to Numba.
    And you sir not only explained to me the concepts in a positive astonishing way, but also gave me the desire and the excitement to apply it on all my old and future codes. Thanks you !
    PS : Is there more videos where you're explaining the others topics ( convolution, neural networks .. )

    • @JackofSome
      @JackofSome  2 ปีที่แล้ว +2

      Great. I hope you share it with your class :)
      Unfortunately no other videos on Numba

  • @trizzzzlez
    @trizzzzlez 2 ปีที่แล้ว +1

    I came back to say a huge thank you. currently doing my Phd. my code was to run 300k iterations it took like 3days+. your short video changed everything, i took few hours to rewrite the code to suit numba as you explained. boom 2hrs i have results on the screen instead of 3days+

    • @JackofSome
      @JackofSome  2 ปีที่แล้ว +1

      That sounds amazing. Please be very careful and do consistency checks between the two codes. Don't wanna find out there was an issue when you're writing your dissertation 😅

    • @trizzzzlez
      @trizzzzlez 2 ปีที่แล้ว

      @@JackofSome yes I will jack thank you.

  • @frodobaggins3974
    @frodobaggins3974 4 ปีที่แล้ว +21

    11:45 - try this: np.zeros_like(input_list, dtype = np.int64, order='C')
    My experience with numba - it works great, but types have to be very precisely defined for every single object. Otherwise nopython will fail, and where numba sucks is generating traceback messages - in the case of complex functions it will take forever to debug. So type whatever you can - it is not a 'Pythonic' way of thinking and writing, but in this particular case it is necessary. Anyway, great introduction!

    • @JackofSome
      @JackofSome  4 ปีที่แล้ว +26

      Thanks for the tip, and best of luck on your journey to mount Doom. We're all counting on you.

    • @0.Andi.0
      @0.Andi.0 2 ปีที่แล้ว +1

      Hi, I have a question, how can I declare like a type so numba can compile it? For example I have a vector3 class that cannot compile with numba (class with x,y,z components)

    • @mariomuysensual
      @mariomuysensual 2 ปีที่แล้ว +1

      @@0.Andi.0 use numpy arrays instead

  • @janewan1196
    @janewan1196 2 ปีที่แล้ว

    Thank you so much! I was trying and failing to turn to C++ for number crunching, but this has just saved me!

  • @b992152
    @b992152 4 ปีที่แล้ว +2

    Great video mate. Really enjoyed it

  • @RealLionTion
    @RealLionTion 3 ปีที่แล้ว +19

    YES, I LOVE PYTHON AND THIS IS PERFECT THANK YOU MATE

  • @dishapandey96
    @dishapandey96 3 ปีที่แล้ว +2

    Your way of explanation is very nice. Excellent video :)

  • @vibhu8024
    @vibhu8024 ปีที่แล้ว +1

    I love how "incredibly fast" python code is pretty much about going back to c/c++ syntax.

  • @SomeFreakingCactus
    @SomeFreakingCactus 2 ปีที่แล้ว +9

    These are some seriously impressive results. I wonder if this could give Python a niche in indie game development.

  • @nahiyanalamgir7056
    @nahiyanalamgir7056 ปีที่แล้ว +1

    Amazing tutorial and Numba is a great software. I hope Python officially will one day ship with a compiler because the community got so huge that people often write performance-intense code in Python that goes against its nature. Moreover, it'd be amazing to ship a Python product statically compiled without gigabytes of libraries!

  • @dadogh
    @dadogh 3 ปีที่แล้ว +5

    That's an awesome video. Thank you! I've been running orekit scripts which took me ~4h, and with numba there are taking ridiculously 2min!

    • @JackofSome
      @JackofSome  3 ปีที่แล้ว +1

      Oh wow those are amazing gains! Glad I could help

    • @shahnawazazam
      @shahnawazazam 3 ปีที่แล้ว

      Just make sure your cpu cores arnt too angy at you

  • @evertonsantosdeandradejuni3787
    @evertonsantosdeandradejuni3787 2 ปีที่แล้ว

    Holy shit, I'm sold. Examples on point, mic indeed touched the ground. Thanks for the tip

  • @MichaelBrown-gt4qi
    @MichaelBrown-gt4qi 3 ปีที่แล้ว +8

    This is amazing. This completely changes python for me.

  • @Shane1994322
    @Shane1994322 3 ปีที่แล้ว

    This video is concise and clear. amazing. Thank you!

  • @Meodoc
    @Meodoc 2 ปีที่แล้ว +2

    I really liked that you stayed real and just said that you aren't qualified to comment on why the python loop with the numpy array took so much longer to execute than just saying something with the risk of talking bullshit and spreading misinformation in order to sound competent, a behaviour I have seen way to often online and which bothers me quite much.
    Very great, clear tutorial, truly one of the best python tutorials I have seen so far on TH-cam. Keep it up! :)

    • @JackofSome
      @JackofSome  2 ปีที่แล้ว +1

      Nice. Yeah it's always better for me to just say "I don't know" when I don't know :)

    • @Meodoc
      @Meodoc 2 ปีที่แล้ว

      @@JackofSome Love it 🙌

  • @hunt9556
    @hunt9556 3 ปีที่แล้ว +4

    Nice tutorial, I'm gonna try numma in my plasma physics simulations

  • @PandemicGameplay
    @PandemicGameplay 3 ปีที่แล้ว

    This is revolutionary. I always wanted a library to allow these but without the hassle of installing something like Cython, etc. Just a good ol' pip lib that can allow my code to speed up orders of magnitude. A nice bonus is the ability to release the GIL.

  • @ianh5537
    @ianh5537 3 ปีที่แล้ว

    Awesome, thanks! Definitely going to start leveraging mumba!

  • @ecielyang9719
    @ecielyang9719 2 ปีที่แล้ว

    I have struggle for Numba for 3 days. This Vedic is really clear

  • @satish-pokala
    @satish-pokala 3 ปีที่แล้ว

    Very clean and informative video. Thank you 🙂👍🏻

  • @dydufjfbfnddhbxnddj83
    @dydufjfbfnddhbxnddj83 2 ปีที่แล้ว

    I didn't understand anything as a beginner to Python (after learning C,C++ and Java) but it looks really cool man. I will use this for python, especially in competitive programming

  • @MVHiltunen
    @MVHiltunen 4 ปีที่แล้ว +14

    numba is really sometimes absolutely stunning in it's acceleration per extra work.

    • @JackofSome
      @JackofSome  4 ปีที่แล้ว

      That it is friend.

  • @palermodpr
    @palermodpr ปีที่แล้ว

    Awesome video man!

  • @pranavramesh7052
    @pranavramesh7052 3 ปีที่แล้ว

    thank you i had a code which took like a whole 5 minutes to start running and now it is much faster

  • @harshraj22_
    @harshraj22_ 4 ปีที่แล้ว +1

    Awesome ! Thanks for this video.

  • @maxmorehead1569
    @maxmorehead1569 4 ปีที่แล้ว +2

    Really great video!

  • @SumitSingh-pu9hd
    @SumitSingh-pu9hd 2 ปีที่แล้ว

    Your video was that amazing and well executed that I was hypnotized to hit subscribe and like. Keep it going.

  • @adityanjsg99
    @adityanjsg99 ปีที่แล้ว

    Presentation level is ingenious!

  • @thestralspirit
    @thestralspirit 2 ปีที่แล้ว +1

    Why wasn't this video in my TH-cam recommendations a year ago?
    Nonetheless, this is an amazing tool for python. I wouldn't have found it without you!

  • @sasimitra5871
    @sasimitra5871 3 ปีที่แล้ว +16

    I don't know why I need this. I'm still a High School student doing python for fun.
    But imma keep this tucked away in my mind.
    I have a feeling I'll need it soon enough.

    • @CrazyFanaticMan
      @CrazyFanaticMan 3 ปีที่แล้ว +8

      When your'e working on projects that needs the program to do things fast, you want C like performance because low level languages like C/C++ are about as fast as you can get.
      Python is not a low level language. It's a high level dynamically typed language. This means it's pretty slow.
      So even though it's pretty fast to write a python program because it's basically the same as writing in English, you're giving up the actual execution speed (performance) in order to keep that fast typing speed (developer performance).
      Numba solves this problem by keeping the Python typing that we all love and getting the C like performance that is needed for projects where speed is very important.

    • @eskees9498
      @eskees9498 3 ปีที่แล้ว +1

      @@CrazyFanaticMan so I'm also in high-school just doing python for fun. Is number useful for smaller projects or only for large projects. My biggest code is only about 80 lines of code, but it uses my Webcam to track hands. Would it be worth it to implement numba for this low amount of code?

    • @CrazyFanaticMan
      @CrazyFanaticMan 3 ปีที่แล้ว +2

      @@eskees9498 It doesn't matter how many lines of code you have, whether it's 80 lines or a billion lines.
      What matters is the problem you are trying to solve. If for example you say "I want my webcam to not only accurately detect the location of my hands but I also want my webcam to track my hands if I move them really fast".
      I would imagine a webcam tracking hands that are moving really fast would require very fast performance speed in order to keep up. So in this case, numba may help you a lot.
      It all really depends on what you want and what your expectations are.
      The size of your program does not matter, numba can you help you whether you're program is big or small

    • @eskees9498
      @eskees9498 3 ปีที่แล้ว

      @@CrazyFanaticMan thank you, I appreciate the info

  • @amir650
    @amir650 ปีที่แล้ว

    Thank you for this excellent presentation.

  • @smjure
    @smjure 3 ปีที่แล้ว

    Great video, learned a lot in 20 min, thanks!

  • @mengzhu8385
    @mengzhu8385 2 ปีที่แล้ว

    Amazing video! I'm starting to think to give numba a try.

  • @culperat
    @culperat 2 ปีที่แล้ว

    Love the video, I'll definitely have to try this on some future projects.

  • @shkhrvarshney
    @shkhrvarshney 2 ปีที่แล้ว

    Awesome tutorial! Thank you so much. I shared the video with my old Intro to Parallel computing professor. Hopefully he sees the email coming from non UW email id lmao. Video would be pretty helpful to any new(&old) students of the course.

  • @KANGAR1982
    @KANGAR1982 3 ปีที่แล้ว

    Great video! subscribed instantly after seeing it!!!

  • @nacnud_
    @nacnud_ 3 ปีที่แล้ว

    Great work dude!

  • @Anonymous9683
    @Anonymous9683 4 ปีที่แล้ว

    Brilliant video, thank you

  • @Rotem_S
    @Rotem_S 3 ปีที่แล้ว

    As someone who tried numba and was disappointed I appreciate you showing possible causes and solutions for that

  • @nobody2937
    @nobody2937 2 ปีที่แล้ว

    Awesome explaination... Thank you ...

  • @foodsscenes5891
    @foodsscenes5891 3 ปีที่แล้ว

    Awesome work!

  • @luisenciso1762
    @luisenciso1762 3 ปีที่แล้ว

    Very helpful video, many thanks :)

  • @pubgplayer1720
    @pubgplayer1720 2 ปีที่แล้ว

    Nice, easy to understand.

  • @vanviethieuanh2237
    @vanviethieuanh2237 2 ปีที่แล้ว

    your tutorial is amazing, thanks!

  • @michaelc3650
    @michaelc3650 2 ปีที่แล้ว +6

    Damn this is really cool, just came across it and it should definitely help in speeding up machine learning or ai projects

  • @Prithvidiamond
    @Prithvidiamond 4 ปีที่แล้ว +2

    Very nice, I like this!

  • @Guilfordust
    @Guilfordust 4 ปีที่แล้ว +5

    This was great, thank you!

  • @MrProzaki
    @MrProzaki 3 ปีที่แล้ว +1

    oh nice, you just gave me lots of work to do xDDDD time to change the whole project code... thanks :'D , no really i mean it THANK YOU it was a great vid will def look into that 10% for sure.

  • @TunkFey
    @TunkFey 2 ปีที่แล้ว

    Thanks for sharing. This video is really a treasure!

  • @NKernytskyy
    @NKernytskyy ปีที่แล้ว

    Amazing Content!

  • @fadillahmaani7413
    @fadillahmaani7413 4 ปีที่แล้ว +2

    Great video, thank you very much ! I hope that you will make numba tutorial for class too.

  • @dyrevennen
    @dyrevennen 2 ปีที่แล้ว

    Thanks for posting the video. I learned something new, and useful.:)

  • @mkthakral
    @mkthakral 2 ปีที่แล้ว

    Fist visit on this channel, but you are the best ;-)

  • @MarkBTomlinson
    @MarkBTomlinson 3 ปีที่แล้ว

    Very interesting presentation and a great boon for an interpreted language.

  • @geraldmerkowitz4360
    @geraldmerkowitz4360 ปีที่แล้ว

    Thanks for the tip, let's try it!

  • @sibyjoseplathottam4828
    @sibyjoseplathottam4828 3 ปีที่แล้ว

    Thank you! You saved me a lot of time.

  • @yf6595
    @yf6595 3 ปีที่แล้ว

    Love this! Thank u very much! will try it out immediately

    • @JackofSome
      @JackofSome  3 ปีที่แล้ว

      Please report back with any gains, and if you have questions you can ask here or on the JackOfSome subreddit :)

  • @Firigion
    @Firigion 3 ปีที่แล้ว

    Okay, I'm hooked. Now i just need this for DDEs.

  • @rodrigoctgouvea
    @rodrigoctgouvea 3 ปีที่แล้ว

    Thanks for the video.

  • @SkyFly19853
    @SkyFly19853 3 ปีที่แล้ว

    Thank you so much for this tutorial!

  • @juanjpnv
    @juanjpnv 2 ปีที่แล้ว

    Thanks, that'll be really helpful to my masters course