Skip to content
View anbarasanhere's full-sized avatar
🎯
Focusing
🎯
Focusing

Highlights

  • Pro

Block or report anbarasanhere

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse

Pinned Loading

  1. AWS-Infrastructure-Copilot-Using-Langchain AWS-Infrastructure-Copilot-Using-Langchain Public

    Developed a conversational AI agent that enables users to manage AWS infrastructure using natural language. The system leverages Claude Sonnet 4.6 to interpret user intent, invoke AWS APIs for serv…

    Python

  2. Streamlit_Car_Price_Prediction_Project Streamlit_Car_Price_Prediction_Project Public

    A Streamlit-based web application that predicts used car prices using machine learning models trained on structured automotive data. It provides an interactive interface where users input features …

    Python

  3. Predictive-Modeling-for-workforce-Retention Predictive-Modeling-for-workforce-Retention Public

    to predict churn rate of OLA drivers

    Jupyter Notebook

  4. Recommendation-Analysis---EDA-through-Python-Libraries Recommendation-Analysis---EDA-through-Python-Libraries Public

    Performed descriptive analytics (NumPy, Pandas) to create a customer profile for each Aero-Fit treadmill product.

  5. Walmart_Confidence_Interval_and_CLT Walmart_Confidence_Interval_and_CLT Public

    Analysed data which has more than 5L+ rows and predicted actionable insights & recommendations. Created interactive visualisation which helps customer retention & acquisition using statistical meth…

  6. Neural-Network-Based-Delivery-Time-Prediction Neural-Network-Based-Delivery-Time-Prediction Public

    A machine learning project focused on predicting intra-city food delivery times using order, restaurant, and partner data. It applies data preprocessing techniques such as datetime feature extracti…

    Jupyter Notebook