Praveen Ramesh

Praveen Ramesh

Machine learning Internship

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location of Praveen RameshSan Francisco, California, United States

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  • Timeline

  • About me

    Machine Learning Engineer at CVS Health - Building GenAI products | Carnegie Mellon University Alumnus | Google Cloud Certified Professional Machine Learning Engineer

  • Education

    • Carnegie Mellon University

      2022 - 2023
      Master's degree Information Systems - Data Science

      Coursework :Machine Learning (10601), Natural Language Processing (11611), Machine Learning in Production (17645), Unstructured Data Analytics , Advanced Business Analytics , Data Focused Python, Intermediate Statistics, Distributed Systems, Object Oriented Programming in JAVA

    • Shanmugha Arts, Science, Technology & Reserch Academy (SASTRA), Thanjavur

      2015 - 2019
      Bachelor of Technology Mechanical Engineering
  • Experience

    • VuNet Systems

      Nov 2018 - Feb 2019
      Machine learning Internship

      • Worked on clustering and anomaly detection of timeseries data using different clustering algorithms - Successfully detected anomalies in server health data. The DBSCAN algorithm was used in clustering one month of server health. Clustering was done based on server CPU usage and memory usage.Visualization of the data was done using kibana and the outliers thrown out by the algorithm was compared with the kibana timelion visualization.• Worked on setting up Apache Spark environment for VuNet's ML platform. Show less

    • Applied Data Finance

      Jun 2019 - Jul 2022
      Senior Data Scientist
    • CVS Health

      Oct 2023 - now
      Machine Learning Engineer
  • Licenses & Certifications

  • Honors & Awards

    • Awarded to Praveen Ramesh
      ADF Technology Hackathon 2021 Applied Data FInance Jun 2021 Third place winner and the first team of data scientists to win the ADF technology Hackathon 2021.
    • Awarded to Praveen Ramesh
      ADF PROMISING DEBUT AWARD 2020 ADF Jan 2021 Awarded with the 2020 ADF Promising Debut Award in recognition of my performance at work