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Shivam6035/README.md

About Me:

I am an adaptable technologist with hands-on experience in machine learning and data analytics. I excel at tackling complex problems, optimizing pipelines, and building scalable, data-driven solutions that drive impactful results across diverse technical domains.

🌐 Socials:

LinkedIn email

💻 Tech Stack:

R Python PowerShell Windows Terminal Bash Script AWS Anaconda FastAPI MySQL MongoDB Postgres Figma Keras Matplotlib mlflow NumPy Pandas Plotly PyTorch TensorFlow Scipy scikit-learn GitHub Actions GitHub Git Docker Kubernetes Postman Power Bi

📊 GitHub Stats:



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  1. Bank-Loan-Report-Analysis Bank-Loan-Report-Analysis Public

    This repository hosts a comprehensive financial loan dataset containing 38,576 records across 24 distinct features. The data provides a granular look at individual loans, encompassing applicant det…

    1

  2. Climate-Change-Trend-Analysis Climate-Change-Trend-Analysis Public

    Analyzed climate change data of past 25 years from year (1995-2019) , Extract Transform & Load data , analyze the change in temperature over years and also find city with max temp in particular yea…

    Jupyter Notebook 1

  3. Customer-churn-prediction-with-PySpark Customer-churn-prediction-with-PySpark Public

    Hands-on customer churn analysis using PySpark. This project showcases the practical application of PySpark for machine learning, focusing on predicting and understanding customer churn.

    Jupyter Notebook 1

  4. EV-sales-analysis-in-tableau EV-sales-analysis-in-tableau Public

    analyzed 150,000 rows of data of electric vehicles and hybrid vehicles including their sales, average mileage, price tag, top manufacturer of car, and ,market share by car over years , states with …

  5. pizza-sales-Analysis pizza-sales-Analysis Public

    Analyzed 5000+ pizza orders, deriving key customer insights and trends to enhance business strategy. Implemented robust data preprocessing, including outlier removal and feature scaling, for optima…

    1

  6. LLM-project LLM-project Public

    Developed a Large Language Model (LLM) with 0.21 million parameters, achieving a training loss of 1.67 and validation loss of 1.83 after 4999 steps on a dataset of over 1.1 million text characters.

    Jupyter Notebook 1