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  • TVS Motors
  • India
  • 03:58 (UTC +05:30)

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vidyasagarbhargava/README.md

Hi, I'm Vidyasagar Bhargava 👋

I’m a Lead Data Scientist at TVS Motor, working for connected mobility solutions department. I have 13+ years of experience in the field of Applied AI where I worked with various clients in developing prescriptive as well as predictive solutions to address core business problems.

Projects

  • Root Cause Analysis for Low Range Trips in EVs
  • Charge Time Estimation
  • Predictive Maintenance of Brakes in two wheelers
  • Range Prediction and Analysis for EVs
  • Cell Imbalance issues in batteries
  • Voice Assistant using RAG and LLMs
  • Churn Prediction in Telecom Industry
  • Price optimization Engine for Scientific Pricing of Fashion Products
  • NPS Improvement using explainable AI
  • Retail store segmentation
  • Anomaly Detection for machine parts failure

Website

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  1. ml-2022 ml-2022 Public

    This Course is designed by me.

    Jupyter Notebook 1

  2. Machine-Learning-Links-And-Lessons-Learned Machine-Learning-Links-And-Lessons-Learned Public

    Forked from adeshpande3/Machine-Learning-Links-And-Lessons-Learned

    List of all the lessons learned, best practices, and links from my time studying machine learning

    1

  3. cs228-material cs228-material Public

    Forked from kuleshov/teaching-material

    Teaching materials for the probabilistic graphical models and deep learning classes at Stanford

    Jupyter Notebook

  4. requests-for-research requests-for-research Public

    Forked from openai/requests-for-research

    A living collection of deep learning problems

    HTML

  5. InferSent InferSent Public

    Forked from HsiaoYetGun/InferSent

    TensorFlow implementation of FAIR's InferSent (Supervised Learning of Universal Sentence Representations from Natural Language Inference Data)

    Python

  6. stanford-tensorflow-tutorials stanford-tensorflow-tutorials Public

    Forked from chiphuyen/stanford-tensorflow-tutorials

    This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.

    Python