Kheem-Dh/RadiologyReportGen-AI

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Created 10 months ago
Updated 10 months ago

Kheem-Dh/RadiologyReportGen-AI

Kheem-Dh

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RadiologyReportGen-AI is an innovative machine learning project focused on automating the generation of radiology reports, specifically tailored for chest X-ray imaging. This repository houses a comprehensive solution that leverages cutting-edge AI techniques, including Vision Transformers (ViT) and GPT-2.

Retrieval-and-Generation-of-Clinical-Insights-from-PDF

The RAFT project integrates Retrieval-Augmented Generation (RAG) with fine-tuning approaches to provide a versatile question-answering system. Leveraging the strengths of OpenAI GPT-3.5 Turbo and Google MedPaLM 2, this framework aims to enhance information retrieval and generation capabilities across various domains.

Jupyter Notebook

Word2Vec-Algorithm-From-Scratch

Skip-Gram Model From Scratch

Jupyter Notebook

RasaNegotiationChatbot

A Rasa-based chatbot designed for automated price negotiation. It skillfully handles conversations to negotiate deals for products like the Samsung Galaxy S10 and iPhone 8, combining natural language understanding with smart negotiation strategies.

Movie-Recommender-System

Jupyter Notebook

Urdu-to-English-Machine-Translation-using-Seq2Seq-Transformers-Variant-Model

This project is aimed at developing a machine translation system for translating Urdu text into English using the Transformer-based architecture.

Jupyter Notebook

Kheem-Dh

Config files for my GitHub profile.

End-End-Object-Detection-By-Using-Transformers-

This paper presents a method for object detection that addresses the problem of direct set prediction. It eliminates the need for multiple components and simplifies the process by avoiding the need for manual intervention.The main components of a framework known as DEtection TRansformer are the transformer and the matching mechanism. This paper shows that the relationship between the two components is strong enough to explain the relationship between the two datasets,The DETR framework achieves a fast R-CNN baseline and is capable of providing uniform panoptic segmentation. It is also well-designed to improve its performance.

Jupyter Notebook

MS-AI-102-Labs-

Welcome to the Microsoft Azure 102 Labs repository, where you'll find a comprehensive set of hands-on labs designed to prepare you for a journey into the world of AI Engineering using Microsoft Azure's powerful AI services. These labs are structured to help you build foundational skills and practical experience in various Azure AI offerings.

Jupyter Notebook

Linear-Exponential-Model-with-Residuals-

Using the admission dataset. Reply the following questions. Using R. 1) Test if there is any relation (linear or exponential) between the following pair of variables: a) SSC Marks Obtained and NU_BS_Test Marks b) SSC Marks Obtained and NU_BS_Test Marks c) SSC Marks Obtained and HSSC Marks Obtained 2) Plot the residual plots for the parts in Question No 1 3) Calculate r2 the each part of question no 1 and confirm it by calculating the same by using the residuals.

GBPS_Dharmani_Colony_Mithi

CV

End-to-End-Implementation-of-a-QA-Bot-using-Deep-Learning

This repository contains the code and resources for an end-to-end implementation of a Question-Answering (QA) bot using deep learning techniques. The project is based on the principles and practices.

Jupyter Notebook

Banking_System

Dharmani

K-Means-PCA-DBSCAN-SVM-Comparsion

Jupyter Notebook

Kheem-Blogs

This is simple react single page application for the blog, where you can add new blogs and also read the existing blogs, with that you have the privellage to delete the existing ones. This approach is for the beginner sand intermediate developers to practice their coding skills. Happy Coding!!

Large-Language-Models-LLMs---Guide

Jupyter Notebook

Kheem_Portfolio

This is my portfolio web page.

Sentiment_Analysis

Bigram-and-Trigram-Modeling

Bigram and Trigram Language Modeling

Jupyter Notebook

Retail-Customer-Churn-Predication-in-R-

Retail data is growing exponentially in variety, volume, velocity & value with each passing year. Smart retailers are well aware that this data can be utilized and eventually holds the prospective for profit. As a result these retailers are becoming more conscious about utilization of data and information kept in their repositories, so they can integrate and analyze these large volumes of data to come up with results that can support the quality of their decision making, in order to stay at a competitive advantage and to increase profits.

Churn-Predication-Pipeline-Using-Azure-Cloud-

Jupyter Notebook

Diabetes-Dataset

Linear and Logistic Regression on Diabetes Dataset

Jupyter Notebook