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Generalized Automatic Pipeline for inspecting and fixing uncertainties in your data

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MLops_G2JN: Automatic Pipeline for fixing uncertainties

Introduction

We present in this repo our pipeline spotting uncertaincies in a given dataset, and then applying automatic solution on inspected epistemic and aleatoric uncertainties.

  • For inspecting uncertainties we use MACEst.
  • For data generation we use SDV.
  • For outliers removal we use PyOD.

Our proposed pipeline

Running the pipeline

In order to activate our pipeline you can do the follwoing steps:

  1. Press Start_G2JN.ipynb
  2. Run the first cell:
%%capture
!pip install macest
!pip install sdv
!pip install pyod
import os
os.kill(os.getpid(), 9)

The kernel will crash and restarts after finishing the installments - thats ok!
3. Run the following cell and watch output:

!git clone https://github.com/gilzeevi25/MLops_G2JN 
%cd MLops_G2JN
!python main.py 

Client's reports

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