Stanford CS230: Deep Learning | Autumn 2018 | Lecture 8 - Career Advice / Reading Research Papers

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  • Опубліковано 11 січ 2025

КОМЕНТАРІ • 27

  • @nirajpudasaini4450
    @nirajpudasaini4450 9 місяців тому +7

    Such a golden lecture. Thanks Andrew - the best teacher in AI.

  • @simonkang7387
    @simonkang7387 2 роки тому +18

    Great lecture. I have got some inspirations. Thank you!

  • @tushihahahi
    @tushihahahi 2 роки тому +20

    Career advice starts at 29:00

    • @akarshrastogi3682
      @akarshrastogi3682 Рік тому +1

      TREASURE ADVICE.
      This has been sitiing on youtube since 2019, I only now viewed it. I regret not knowing this earlier.

  • @abrahamowos
    @abrahamowos 2 роки тому +17

    "Those things do not as directly contribute to this" 😂😂

  • @MinimalRevolt
    @MinimalRevolt Рік тому +12

    Wish I could migrate to U.S from Malaysia and study at Stanford. Need to surround more with intellectual societies who values the truth of knowledge, not mythological of ignorance.

  • @mohamadzakaria6637
    @mohamadzakaria6637 Рік тому

    Very inspiring! Lot of stuffs I have missed here :)

  • @lone0017
    @lone0017 11 місяців тому +1

    I wish I saw this 4 years ago

  • @omar.sultan
    @omar.sultan 2 роки тому +4

    This was inspiring. Thank you

  • @Will29295
    @Will29295 Рік тому +2

    If we are kind of new. How to we go about compiling a reasonable list of papers especially papers that cover some of the more basic topics?

  • @EmiTheLoomistar
    @EmiTheLoomistar 2 роки тому +6

    Andreeew!!

  • @klindatv
    @klindatv 7 місяців тому +1

    Well, he didn't explain if you have to be wide or deep on topics. Probably he advises to do a trade-off.

  • @aricircle8040
    @aricircle8040 10 місяців тому

    Great lecture! Are there also lectures about how to perform research/write a paper?:)

  • @MuhammadOmar-qx6nh
    @MuhammadOmar-qx6nh 7 днів тому

    11:00

  • @muhammadumarsotvoldiev8768
    @muhammadumarsotvoldiev8768 Рік тому +1

    Great!

  • @fgfanta
    @fgfanta 2 роки тому +21

    3 years later, with the demand for MLOps and ML in the cloud, and models democratization, this hasn't aged well, not outside of academia at least.

    • @TheFinalVenue
      @TheFinalVenue 2 роки тому +2

      Interesting. What would your advice be?

    • @fgfanta
      @fgfanta 2 роки тому

      @@TheFinalVenue Here, straight from the horse's mouth ua-cam.com/video/06-AZXmwHjo/v-deo.html

    • @ngocminhdoan9655
      @ngocminhdoan9655 2 роки тому +2

      I'm new to this, could you elaborate a little bit on what you meant?

    • @itaymargolin1436
      @itaymargolin1436 2 роки тому +13

      ​@@ngocminhdoan9655
      My guess that he meant that in industry, knowing how to utilize and deploy models has become more important than understanding the math behind them.
      In my opinion, this is partially correct. You can create a wonderful zero shot recommendation systems, chatbots and descent cv-based solutions without a single training loop.

    • @ngocminhdoan9655
      @ngocminhdoan9655 2 роки тому +3

      @@itaymargolin1436 Thank you so much for your explanation

  • @Watermelon-n6y
    @Watermelon-n6y Рік тому +1

    34:00

  • @pavel.pavlov
    @pavel.pavlov Рік тому +2

    This is wrong. First you check if there is a ready model or API for this problem

  • @Memarathi56
    @Memarathi56 Рік тому

    Sandeep sir video dekh ke koi aaya hai