What Partial Derivatives Are (Hands-on Introduction) - Topic 67 of Machine Learning Foundations

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  • Опубликовано: 9 фев 2025
  • #MLFoundations #Calculus #MachineLearning
    This video is a complete introduction to partial derivatives. To make comprehension of what can be a tricky subject as easy as possible, we use a highly visual combination of colorful paper-and-pencil examples, hands-on code demos in Python, and an interactive click-and-point curve-plotting tool.
    There are eight subjects covered comprehensively in the ML Foundations series and this video is from the fourth subject, "Calculus II: Partial Derivatives & Integrals". More detail about the series and all of the associated open-source code is available at github.com/jonkrohn/ML-foundations
    The playlist for the Calculus subjects is here: • Calculus for Machine L...
    Jon Krohn is Chief Data Scientist at the machine learning company Nebula. He authored the book Deep Learning Illustrated, an instant #1 bestseller that was translated into six languages. Jon is renowned for his compelling lectures, which he offers in-person at Columbia University, New York University, and leading industry conferences, as well as online via O'Reilly, his RUclips channel, and the SuperDataScience podcast.
    More courses and content from Jon can be found at jonkrohn.com.

Комментарии • 22

  • @jiezhao2046
    @jiezhao2046 Год назад +4

    Just finished Calculus one. I appreciate how the courses are broken down into smaller chunks. It makes learning and focusing much easier. I also love the fact that Jon always brings up the main agenda at the beginning of the video and provides a summary of what we have covered in the end. It's very helpful for understanding where the knowledge fits into the bigger picture without getting lost in it. Thank you for providing such great content.

    • @JonKrohnLearns
      @JonKrohnLearns  Год назад +2

      Congrats on finishing the Calculus series, Jie Zhao, and delighted that you've been enjoying the videos. I can't wait to release more videos from my ML Foundations curriculum (e.g., on probability theory, statistics and computer science) soon.

  • @aashishrana9356
    @aashishrana9356 3 года назад +5

    I was literally struggling hard to understand partial derivatives from last few days.
    And this video was end of my struggle.
    I bet, no one can explain partial derivatives better than you with such a intuitive visualization.
    Thanks a lot Jon!

    • @JonKrohnLearns
      @JonKrohnLearns  3 года назад +1

      Yay! You're welcome, Aashish. So glad my visual/intuitive approach to partial derivatives worked for you :)

  • @justsimple2223
    @justsimple2223 Год назад +1

    I can’t express how much I am obsessed with math because of you. Thanks :)
    but disappointed by not completing the full series.

  • @mohamadnawfal8047
    @mohamadnawfal8047 2 года назад +1

    very useful lesson, Although I have studied partial derivatives previously, your videos made me have better understanding of it, especially the code demos.
    many thanks

  • @basha132
    @basha132 3 года назад +4

    I love your courses & video so much

    • @JonKrohnLearns
      @JonKrohnLearns  3 года назад +2

      Awesome, Muneer! It's my pleasure to serve you - I hope I can continue to produce content that you love!

  • @ButterBeanCW
    @ButterBeanCW 2 года назад +2

    This is the first time in my life where I’m excited about calculus because it’s being applied to something I’m interested in. Thanks for this really clear explanation.

    • @JonKrohnLearns
      @JonKrohnLearns  2 года назад +1

      So awesome to hear this, Corey - keep on rockin' :)

  • @gaurew
    @gaurew Год назад +1

    I understood everything unitl i reached hands on code demo...The functions and all these graph functions are blowing my mind

    • @JonKrohnLearns
      @JonKrohnLearns  Год назад +1

      I'm glad to hear that the initial part of the video was clear to you! The hands-on coding demos can be quite complex, especially the graph functions. I didn't want to spend too much time on that code as I suspect most people are watching the videos for the Calculus content. My recommendation would be to paste my code into GPT-4 and ask clarifying questions.

    • @gaurew
      @gaurew Год назад

      @@JonKrohnLearns Thanks Jon for responding means a lot...I was completing the series via O'Reilly but had doubt...Like .I haven't study DSA anything...So your series included DSA..So should i study DSA separately on my own and then complete the series..I guess DSA is important for optimization ..which is a further topic in your ML foundation series..

  • @fmikael1
    @fmikael1 3 года назад +4

    You're doing God's work mate!

  • @younesqasempour2282
    @younesqasempour2282 3 года назад +1

    I loved this session!!!
    Special thanks for all your effort's.💙💙

    • @JonKrohnLearns
      @JonKrohnLearns  3 года назад

      You're most welcome, Younes! This particular video's one of my favorites so I'm glad it resonated with you :)

  • @d.s.5157
    @d.s.5157 Год назад

    When would you get the answer -1 when dealing with partial derivatives ?

  • @shekharpandey844
    @shekharpandey844 3 года назад +2

    Sir, I need to start calculus from beginning, plz suggest i

    • @JonKrohnLearns
      @JonKrohnLearns  3 года назад +2

      Perfect! Then my "Calculus for ML" playlist is what you need to start from scratch. Here it is: ruclips.net/p/PLRDl2inPrWQVu2OvnTvtkRpJ-wz-URMJx

  • @stijnwuyts6733
    @stijnwuyts6733 9 месяцев назад

    Y = mx + b. What this has 2 variables? This has one variable x and 2 parameters? This is univariate equation?