Dynamic Pricing using Machine Learning Demonstrated

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  • Опубликовано: 21 дек 2024

Комментарии • 33

  • @arriyad1arriyad649
    @arriyad1arriyad649 Месяц назад

    Very interesting how clustering can be used in feature engineering. Is there a reason why the clusters are used as one-hot (Y/N). Is this due to the fact that we wanted a binary decision tree?

    • @DataScienceDemonstrated
      @DataScienceDemonstrated  Месяц назад

      Hi, Thanks. The clusters are independent of each other - i.e handbags cluster of is independent from footwear cluster. So one-hot encoding is preferred approach

  • @shadeersadikeen1052
    @shadeersadikeen1052 7 месяцев назад +2

    Can you share the source code to. how to build a smart pricing model. because there is no video can be found in the youtube =.

  • @doitandmakemoney7039
    @doitandmakemoney7039 Год назад +1

    thanks, sir for the content. can you please share the link to the dataset?

  • @WojciechDynda
    @WojciechDynda 3 месяца назад

    Great introduction to the topic, any more advanced instruction about tehcnical part?

  • @karannchew2534
    @karannchew2534 Год назад +2

    Sound quality can be improved.

  • @randyhaluong
    @randyhaluong Год назад +1

    hi, thank you for the vivid explanation. may i ask a question: which software are you using to group different product items into clusters, and then visualize those clusters with color on the x,y coordinate?

    • @DataScienceDemonstrated
      @DataScienceDemonstrated  Год назад

      Thanks! I have created my own platform , which is based on Python and JavaScript visualization libraries. You can access it here : experiencedatascience.com . You will be able to make similar clustering and visual as I have shown, without coding. Hope you enjoy it

  • @andrejk9523
    @andrejk9523 3 года назад +2

    Is there a git repo available?

    • @DataScienceDemonstrated
      @DataScienceDemonstrated  3 года назад

      Hi Andrew, I am putting all demos in my videos on channels website www.experiencedatascience.com
      You will find some of the functionalities on this website

  • @JunaidAhmed-jd5kq
    @JunaidAhmed-jd5kq 4 месяца назад

    Hey, Where can I get this dataset?

    • @DataScienceDemonstrated
      @DataScienceDemonstrated  4 месяца назад

      @@JunaidAhmed-jd5kq Hi, you can get it from here www.kaggle.com/c/mercari-price-suggestion-challenge

  • @gustavobio
    @gustavobio 3 года назад +2

    Hi, just found out this channel. AMAZING resource for us aspiring DS trying to build portfolios. The way you clearly explain the business problem and how the DS solution delivers value is invaluable for people like me with little domain knowledge. Thank you!

  • @emilymyers9676
    @emilymyers9676 3 года назад +3

    Thanks, very good subject and great visuals !

  • @jimbocho660
    @jimbocho660 3 года назад +2

    A very nice talk, but shouldn't the demand, which is usually both price and time dependent, also be taken into consideration when dynamically setting a price?

    • @DataScienceDemonstrated
      @DataScienceDemonstrated  3 года назад +2

      Thanks Jim. Yes in many cases you can use demand an input parameter of machine learning model to determine the price. However in cases where demand cannot be directly determined (specially incase of e-commerce marketplace scenario), then other parameters help in building the machine learning model

    • @jimbocho660
      @jimbocho660 3 года назад +1

      @@DataScienceDemonstrated Thanks a lot for the response. Are these other parameters used to build the ML model price and time dependent, like demand? Can you give some examples of these parameters? And how frequently are these ML based dynamic pricing models updated?

    • @DataScienceDemonstrated
      @DataScienceDemonstrated  3 года назад

      Hi Jim, paramètres could be time dependent (like demand) or non time dependent. Some examples are product description, ratings, location etc… More the input parameters, better it is. Then machine learning will automatically detect which are more important than others

  • @517127
    @517127 Год назад

    And How can we optimize this price ?

    • @DataScienceDemonstrated
      @DataScienceDemonstrated  Год назад

      Hi, you will need demand data , which can be as an input feature to your model. The output price is optimized based on the demand

  • @raulmoreno9204
    @raulmoreno9204 3 года назад +2

    Fantastic ! Very clear explanation !

  • @anuptotla9845
    @anuptotla9845 3 года назад +3

    Fantastic clear explaination sir. Which tool do you use to create these visualisations? Seems pretty cool. Can it also be used to experiment with various models visually?

    • @DataScienceDemonstrated
      @DataScienceDemonstrated  3 года назад

      Thank you Anup. I use Python and JavaScript to create visualization. I have started to put the functionalities on channels website experiencedatascience.com . It will allow you to make visuals on your data in a easy way

  • @rrrfamilyrashriderockers6891
    @rrrfamilyrashriderockers6891 10 месяцев назад

    very interesting can you share github code

  • @leowarpride9133
    @leowarpride9133 2 года назад +2

    Dude; I hope you get more and more subscribers to encourage and finance you to produce more such great content. Kudos and thanks✊️

    • @DataScienceDemonstrated
      @DataScienceDemonstrated  2 года назад

      Thank you very much! Much appreciated

    • @leowarpride9133
      @leowarpride9133 2 года назад +1

      @@DataScienceDemonstrated feel like you are a telco fella (like me) (Re your telco data based demonstrations). Would be great if you could make yet another video explaining how the decision tree is modeled actually. Cause as Far as I understand the decision tree is used to train ML in trial-error-learn fashion which fairly understood thx to your video but the technique to model the tree and if it can be performed by another preliminary AI technique is not clear to me. Thanks in advance chief✊️😊

  • @SuperMsmystery
    @SuperMsmystery 2 года назад

    Good content,and I can't watch it because of mouth sounds.