Implementation of RIFT-SVC, a singing voice conversion model based on Rectified Flow Transformer.

categorizing news: fake or not

Compare SVM mode yoga movement classification accuracy with Linear kernel, Polynomial kernel, RBF (Radial Basis Function) kernel, LSTM with accuracy up to 98%. In addition, it also supports adjusting the practitioner's movements according to standard movements.

A Natural Language Processing Project: Use NewsAPI to gather URL's of news articles, along with webscraping, gather news articles and generate a bias classifier to then run on news sources that are considered "centered" by AllSides Media to determine the validity of that classification.

Customer churn prediction is the process of using machine learning models to identify customers who are likely to leave in the near future.

Our first participation in a Kaggle competition. Dry Beans Classification is an unranked competition held by ITI AI-Pro.

EDA and Prediction of F1 Race WInners

This resume analysis website would help you select your desired candidate through a sea of applicants.Along with it, it will also help you detect the personality of the candidate through OCEAN model.

Data fetched by wafers is to be passed through the machine learning pipeline and it is to be determined whether the wafer at hand is faulty or not apparently obliterating the need and thus cost of hiring manual labour.

In this prototype, credit card approval data was analysed and a machine learning model was created to forecast the approval of credit card requests.

IntelliCV is an AI-driven platform for efficient and intelligent resume screening.

Models bank loan applications to classify and predict approval decisions using customer demographic, financial, and loan data. Applies machine learning algorithms like logistic regression and random forest for enhanced automation.

Predicting Diabetes with Machine Learning Techniques

This project aims to use machine learning models on Kaggle data to predict corporate credit ratings to aid investment decisions.

A classification problem for monochrome images solved using different machine learning methods (Naive Bayes, KNN, SVC, Neural Network, Convolution Neural Network).

Medicine recommendation system is a wounderful machine learning project that provides a web interface for the user to enter the details of the symptoms and according to the symptoms it generates the disease type and respective medication, diet, workout, description of the disease

iNeuron DataScience Internship: During this Internship, I have worked on project related to Data Analytics field in which logistic regression, decision tree and support vector machine have been used for classification problem

Diabetes is a medical disorder that affects how the body uses food for energy. When blood sugar levels rise, the pancreas releases insulin. If diabetes is not managed, blood sugar levels can rise, increasing the risk of heart attack and stroke. We used Python machine learning to forecast diabetes.

Machine learning techniques are increasingly applied in the classification of drugs based on biomarkers related to epileptic seizures. Various studies highlight the use of deep learning and other machine learning models to enhance seizure detection and classification from EEG data.