Foundation of Q-learning | Temporal Difference Learning explained!

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  • Опубликовано: 27 ноя 2024

Комментарии • 26

  • @PrymeOrigin
    @PrymeOrigin 11 месяцев назад +20

    You have a gift to teach and I'm very thankful to find someone who breaks down concepts so simply and easy
    to digest

  • @noahgsolomon
    @noahgsolomon 7 месяцев назад +8

    The breakdown of the 1 sentence explanation is so useful

  • @LuthandoMaqondo
    @LuthandoMaqondo Год назад +8

    Nice, quick and straight to the point.

  • @al_parlam
    @al_parlam 10 месяцев назад +2

    man, your explanation is gorgeous ! you are remarkable in explaining complex things. Keep doing what you are doing :) I wish you much luck with your channel

  • @LaveshNK
    @LaveshNK 9 месяцев назад

    Fantastic video...I have a RL assignment due and I had no idea wht TD error even meant. You are great at explaining

  • @pareak
    @pareak Месяц назад

    I'll need to check out more of your videos... That is so well explained!!

  • @benjaminimsi9558
    @benjaminimsi9558 3 месяца назад +2

    i wasnt expecting such a good explanation.

  • @slitihela1860
    @slitihela1860 9 месяцев назад +1

    can you prepare a video for Double Q-Learning Network
    and Dueling Double Q-Learning Network
    please

  • @DevanshSagar-cy8kp
    @DevanshSagar-cy8kp 5 месяцев назад +1

    Great work ❤

  • @gregkondas6457
    @gregkondas6457 2 месяца назад

    thank you so much! this is an awesome resource!

  • @manojkumar-pp4ky
    @manojkumar-pp4ky 4 месяца назад +1

    Excellent

  • @akshaypansari111111
    @akshaypansari111111 Год назад

    Thanks a lot. This is real helpful. I will check out the bellman equation video as well

  • @yep3659
    @yep3659 8 месяцев назад +1

    I'm craving for some Tempuras now

  • @li-pingho1441
    @li-pingho1441 Год назад

    awesome explanation!

  • @minapagliaro7607
    @minapagliaro7607 7 месяцев назад

    Great video !!!!

  • @krishnavinukonda1882
    @krishnavinukonda1882 7 месяцев назад

    This is best . Thanks!

  • @krzysztofjarek6476
    @krzysztofjarek6476 Год назад

    Great lecture 😉

  • @Trubripes
    @Trubripes 3 месяца назад

    why use an episodic problem as an example for 1-step TD ? the advantage of TD is for non-episodic problems.
    TD uses previous value to bootstrap the current estimate, in this case shouldn't the table be initialized to R for each S,
    instead of zeroes ?

  • @kmishy
    @kmishy 4 месяца назад +1

    this video not ust explain q value, but also value function, action value function, episode, etc

  • @davidlieber3494
    @davidlieber3494 11 месяцев назад

    great video, thanks!

    • @CodeEmporium
      @CodeEmporium  11 месяцев назад

      You are very welcome. Thanks for commenting

  • @redrose5406
    @redrose5406 Год назад

    Post more about GANs

  • @satyamdubey4110
    @satyamdubey4110 9 месяцев назад

    💖💖

  • @razainul
    @razainul Месяц назад

    why haven't you given true credits to the original video creator. The voice is not yours we know it. You are simply lip-syncing the audio. You could've used the video and used your own true voice! I feel this is not your voice! 99.99% !