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About me



  • 2020 - 2023
    Digital Tesseract

    ML & AI Intern

    Analyzed customer data, segmented the customers into 4 key segments, predicted buying behavior of clients, modeled purchase incidence, brand choice of 5 brands and quantity bought.
    Obtained 90% accuracy in estimating sale of audiobooks.
    Examined 30,000 tweets from Twitter to determine sentiment with a custom-built training model.

  • 2020 - 2020
    R.V. College of Engineering

    Machine Learning Research Intern

    Enabled plant reconstruction by applying CNN obtaining an RMSE of 0.05 utilizing OpenCV.
    Implemented K-means clustering and Naïve Bayes to understand and predict 10 plant features.
    Performed histogram analysis of color space with 9 color variants.