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  • KPMG
  • Seattle, WA, USA



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  1. Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.

    Python 2k 626

  2. Short Tutorial to Probabilistic Graphical Models(PGM) and pgmpy

    Jupyter Notebook 305 190

  3. The second home for content from the Practical Statistics course. All content has actually been prepared in Colab, but is shared here.

    Jupyter Notebook

  4. Capstone Project completed as a part of the Microsoft Professional Program for Data Science. This report explores the problem of predicting earthquake damage.

    Jupyter Notebook 3

  5. Notes and code from Data Science and Big Data Analytics: Making Data-Driven Decisions, a course by MIT xPro.

    Jupyter Notebook 6 8

4 contributions in the last year

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Contribution activity

January 2022

mrklees has no activity yet for this period.

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