Skip to content
View P101010's full-sized avatar

Block or report P101010

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.

Please don't include any personal information such as legal names or email addresses. Maximum 100 characters, markdown supported. This note will be visible to only you.
Report abuse

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

Report abuse

Pinned Loading

  1. Brain-Tumor-Classification-Production-Ready-App Brain-Tumor-Classification-Production-Ready-App Public

    Forked from Omii2899/Brain-Tumor-Classification

    This project is designed to develop, deploy, and maintain a machine learning model using MLOps best practices and industry standard tools.

    Python

  2. RAG-SQL-Assistant RAG-SQL-Assistant Public

    The RAG SQL Assistant is a tool designed to assist users in generating queries to interact with SQL databases using natural language queries.

    Python

  3. Multimodal-Document-Retrieval Multimodal-Document-Retrieval Public

    How do you query a pdf document which includes information in visualizations? This is what we are trying to implement leveraging ColPali.

    Jupyter Notebook

  4. Document-Retrieval-Leveraging-SPARC-technique Document-Retrieval-Leveraging-SPARC-technique Public

    This is a document retrieval system implementation that combines the strengths of both sparse and dense representations to effectively rank documents based on their relevance to a given query.

    Jupyter Notebook

  5. Classical-Machine-learning-Algorithms Classical-Machine-learning-Algorithms Public

    This repository contains the implementation of classical machine learning algorithms from scratch using Python and libraries such as NumPy, Matplotlib, and SciPy

    Jupyter Notebook

  6. Predicting-the-load-on-a-bus Predicting-the-load-on-a-bus Public

    In this machine learning project, we are trying to help MBTA solve these problems by building a model to answer below questions: 1. What is the predicted load of a bus on a particular date and time…

    Jupyter Notebook