RajanikaD

Analysis-on-Covid-19

Showing how data analysis can be utilized in anticipating the new day by day instances of Corona Virus.

Arrhythmia-Classification-Using-Machine-Learning

This project classifies arrhythmia using the UCI dataset with 279 features and 452 examples. It predicts if a person has arrhythmia and classifies it into 12 types. The notebook includes data preprocessing, feature selection, and machine learning model implementation for accurate medical data prediction.

Brain-Tumor-Detection.ipynb

The main purpose of this project was to build a CNN model that would classify if subject has a tumor or not base on MRI scan. I used the VGG-16 model architecture and weights to train the model for this binary problem.

CNN-Model-Fashion

CNN-model for fashion classification

Document-Classifier

Identifies the document if they are Pan Card or not.

Face-mask-detection-model

German-Credit-Analysis-and-Prediction

Model that will help classify a person, based on the attributes as good or bad credit risk.

Great-Barrier-Reef-Kaggle

Object detection model that accurately identifies starfish in real-time by training on underwater videos of coral reefs.

Image-Classification-Model-

Here I have built a model which classifies and identifies which images are of cats and dogs.

sales_predictions

Predicting the sales of various cars using Linear Regression

RajanikaD/Analysis-on-Covid-19

Showing how data analysis can be utilized in anticipating the new day by day instances of Corona Virus.

RajanikaD/Arrhythmia-Classification-Using-Machine-Learning

This project classifies arrhythmia using the UCI dataset with 279 features and 452 examples. It predicts if a person has arrhythmia and classifies it into 12 types. The notebook includes data preprocessing, feature selection, and machine learning model implementation for accurate medical data prediction.

RajanikaD/Brain-Tumor-Detection.ipynb

The main purpose of this project was to build a CNN model that would classify if subject has a tumor or not base on MRI scan. I used the VGG-16 model architecture and weights to train the model for this binary problem.

RajanikaD/CNN-Model-Fashion

CNN-model for fashion classification

RajanikaD/Document-Classifier

Identifies the document if they are Pan Card or not.

RajanikaD/Face-mask-detection-model

RajanikaD/German-Credit-Analysis-and-Prediction

Model that will help classify a person, based on the attributes as good or bad credit risk.

RajanikaD/Great-Barrier-Reef-Kaggle

Object detection model that accurately identifies starfish in real-time by training on underwater videos of coral reefs.

RajanikaD/Image-Classification-Model-

Here I have built a model which classifies and identifies which images are of cats and dogs.

RajanikaD/Predictive-Modeling-using-Logistic-Regression-A-Data-Driven-Approach-to-Classification

A project showcasing the development and deployment of a Logistic Regression model using Scikit-Learn. The model is converted to ONNX format for cross-platform deployment, ensuring efficient and reliable predictions. Includes data preprocessing, model training, and validation steps with a focus on production readiness.

RajanikaD/sales_predictions

Predicting the sales of various cars using Linear Regression

RajanikaD/Speech-Analyzer

RajanikaD/Assistive-Technology-for-Deaf-and-Dumb

Sign Language Detector

RajanikaD/Blind-Assistance-Object-Detection-and-Navigation

This is a vision enhancer based module specifically for the BLIND VICTIMS. The system is designed in such a way in which the blind person can take the help of THIRD PARTY APPLICATION which sends Real Time Frames to the LAPTOP-BASED WIRELESS NETWORKED SYSTEM. It works on REAL-TIME OBJECT DETECTION using SSD_MOBILENET algorithm and TENSORFLOW APIs . It has a core feature of approximate distance calculation and Voice - Based wireless feedack generation w.r.t the DISTANCE CALCULATION. It makes the work of Blind easy,efficient and reliable by sending wireless Voice based feedback whether the particular object is either too close to him or is it at a safer distance. The same system can be used from Obstacle Detection

RajanikaD/Classification-of-Arrhythmia-using-ECG-Data

Developed accurate and efficient machine learning algorithms for automated arrhythmia detection and classification. The goal is to predict if a person is suffering from arrhythmia or not, and if yes, classify it in to one of the available groups.

RajanikaD/Data-Visualization-IITDV

RajanikaD/FroshLink_Task1

RajanikaD/gettingStartedWithGithubInMR

RajanikaD/Hand-Gestures

RajanikaD/MentorIF

RajanikaD/Object-Detection

This project performs object detection on shelf images using OpenCV and a pre-trained YOLOv3 model. It detects common objects (e.g., bottles, books) and displays bounding boxes with labels. The model is based on the COCO dataset, and the output image with detections is saved for further analysis or display.

RajanikaD/Occupancy

RajanikaD/Portfolio2.0

RajanikaD/PortfolioRD

RajanikaD/rajanika.github.io

RajanikaD/RajanikaD

RajanikaD/RajanikaD-Website

RajanikaD/RealTimeObjectDetection

RajanikaD/Resume-Analyzer

A resume analyzer using regular expressions to extract specific information out of a resume.

RajanikaD/UCL_AISOC_Tutorial_HandGestureRecognition

This project aims to design a real-time vision-based hand gesture recognition system with machine learning techniques, which potentially makes deaf-and-mute people life easier.