Engineering Python 18A: Optimization using SciPy

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  • เผยแพร่เมื่อ 14 พ.ย. 2024

ความคิดเห็น • 20

  • @YongWang
    @YongWang  4 ปีที่แล้ว

    I found a bug in 18A_Optimization_using_SciPy.ipynb and fixed it on 11/18/2020. The old file stops running after [In 11] due to an error "NameError: name 'x0' is not defined". Please download the updated file.

    • @anirudhmalik5107
      @anirudhmalik5107 3 ปีที่แล้ว

      Can I get your LinkedIn or anything, just want to talk about a problem in my question!!

  • @MrMaipeople
    @MrMaipeople 5 ปีที่แล้ว +1

    The best optimisation ever. Straight to point. No nonsense. No bullshit. Thank you very much.

    • @YongWang
      @YongWang  5 ปีที่แล้ว

      Thanks, Inusa.

  • @maudentable
    @maudentable 6 ปีที่แล้ว +3

    Best lectures ever. Simple and directly to the point.

    • @YongWang
      @YongWang  5 ปีที่แล้ว

      Thanks for the comment, Mauladous

  • @ungerspiltz4586
    @ungerspiltz4586 5 ปีที่แล้ว

    Refreshingly concise tutorial

  • @YongWang
    @YongWang  5 ปีที่แล้ว +3

    Hi Guys, please comment and let me know what you think about this Engineering Python open course. If you enjoy the video, please subscribe and share with your friends. Thanks!

    • @abelermias445
      @abelermias445 5 ปีที่แล้ว

      A part-time graduate student in engineering is enrolled in a four-unit mathematics course
      and a three-unit design course. Since the student has to work for 20 hours a week at a
      local software company, he can spend a maximum of 40 hours a week to study outside
      the class. It is known from students who took the courses previously that the numerical
      grade (g) in each course is related to the study time spent outside the class as gm = tm/6
      and gd = td/5, where g indicates the numerical grade (g = 4 for A, 3 for B, 2 for C, 1 for
      D, and 0 for F), t represents the time spent in hours per week to study outside the class,
      and the subscripts m and d denote the courses, mathematics and design, respectively.
      The student enjoys design more than mathematics and hence would like to spend at least
      75 minutes to study for design for every 60 minutes he spends to study mathematics.
      Also, as far as possible, the student does not want to spend more time on any course
      beyond the time required to earn a grade of A. The student wishes to maximize his grade
      point P, given by P = 4gm + 3gd, by suitably distributing his study time. Formulate
      the problem as an LP problem.
      could you please, solve this problem using python programming and send me the file in "ipynb" format on this email "arbaminchuermias@gmail.com".....thankyou very much.....i need help please

  • @AJ-et3vf
    @AJ-et3vf 3 ปีที่แล้ว

    Very helpful and useful! Thank you sir!

  • @lux27.42
    @lux27.42 4 ปีที่แล้ว

    saved to my playlist, thank you so much, sir :)

  • @py_tok5589
    @py_tok5589 4 ปีที่แล้ว

    NICE, DR Wang this is my new Yt channel

  • @rahdar2008
    @rahdar2008 4 ปีที่แล้ว

    keep in, on TH-cam the best stuff gets very little attention. keep it up.

  • @金成柱김성주
    @金成柱김성주 4 ปีที่แล้ว

    Thanks for the video, could you explain about the [xopt, fopt, ....]=\ command? Thanks.

  • @lucasdetogni4392
    @lucasdetogni4392 2 ปีที่แล้ว

    If i wanna use 2 or (n) parameters, how can i do it? Could you explain this solver to f(X,Y,Z,W,...)

  • @sriharshakodati
    @sriharshakodati 4 ปีที่แล้ว

    This is awesome! May I know how to use constraints for fsolve function?
    For example how do we mention that we need the roots to be not negative for the example at 5:24 ?
    Thanks!!

  • @windguru22
    @windguru22 5 ปีที่แล้ว +1

    Yong, how would we add constraints?

  • @hassane_azzi
    @hassane_azzi 4 ปีที่แล้ว

    Very good course ! Thankyou

    • @YongWang
      @YongWang  4 ปีที่แล้ว

      thanks, hassane

  • @ifeanyiokwuazu3225
    @ifeanyiokwuazu3225 3 ปีที่แล้ว

    Please I am relatively new to data science....but why do most videos use generated datasets rather than actual data from Kaggle or any other site?
    Does this really help when a real problem is encountered in the real world ?