ML System Design: Feature Store

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  • เผยแพร่เมื่อ 23 พ.ย. 2024

ความคิดเห็น • 11

  • @saketthavanani312
    @saketthavanani312 3 ปีที่แล้ว +2

    Great Explanation!!

  • @sunilbelde6290
    @sunilbelde6290 3 ปีที่แล้ว +1

    Does this feature store concept works only where it has tabular data features or can it be used for tasks related to computer vision(images) and nlp(text files)

    • @AppliedAICourse
      @AppliedAICourse  3 ปีที่แล้ว +2

      You can use it for text and image features also, You can simply store the deep-learning based dense features in the feature-store.

  • @vigneshvicky8732
    @vigneshvicky8732 3 ปีที่แล้ว +1

    Good one.
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    Congratulating u for making good replies to those who questions u....

    • @AppliedAICourse
      @AppliedAICourse  3 ปีที่แล้ว +1

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  • @cloudy_data_engineer
    @cloudy_data_engineer 3 ปีที่แล้ว

    Awesome explaination

  • @vighneshsablok5851
    @vighneshsablok5851 3 ปีที่แล้ว

    The Key value pairs in FS used for Model serving will have a fixed subset of features out of all features. How can we call another model with different features using the same Feature Store.

    • @AppliedAICourse
      @AppliedAICourse  3 ปีที่แล้ว +2

      The value in the hash table typically contains all features. For Model Serving, we can pick those those features that our model needs from the full set of features.

  • @srikanthv7781
    @srikanthv7781 3 ปีที่แล้ว

    Can you make a video on how to make portfolio projects?

    • @AppliedAICourse
      @AppliedAICourse  3 ปีที่แล้ว +1

      Please check this: th-cam.com/video/wfF4BDQd7ig/w-d-xo.html

  • @vikrantmohite1226
    @vikrantmohite1226 3 ปีที่แล้ว

    Nice