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  1. An exploratory analysis of Kaggle's 2018 Data Science Survey with over 20,000 respondents.

    Jupyter Notebook

  2. Find donors for an NGO using data about individuals using supervised machine learning

    HTML 1

  3. Unsupervised learning to help a business identify customer segments and implement A/B tests to increase spending per customer segment.

    HTML 1

  4. This notebook Implements of Actor/Critic policy gradient methods to control a Quadcopter in a continuous action space.


  5. This is a deep convolutional neural network used to classify an image data-set of over 153 different dog species.

    HTML 1

  6. Solve Kaggle Data Challenge by implementing most supervised machine learning algorithms and basic neural networks.

    Jupyter Notebook 1

315 contributions in the last year

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Contribution activity

January 2022

6 contributions in private repositories Jan 6 – Jan 15

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