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

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.

categorizing news: fake or not

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.

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.

Predicts Forsyth–Edwards Chess Notation from a chess board image, using a C-SVC 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.

EDA and Prediction of F1 Race WInners

Predicting Diabetes with Machine Learning Techniques

Heart Disease Predictor using Linear regression, Logistics and Support Vector Algorithm in Python.

Demystify Cuisine and Culture From Ingredients using Natural Language Processing and Machine Learning | Python, Pandas, Matplotlib, NLTK, scikit-learn, webscraping, Python Flask-powered API backed by PostgreSQL, Front-end with HTML, CSS, and Javascript

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

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.

This repository contains a machine learning project aimed at predicting diabetes using various algorithms such as Decision Tree Regression, Support Vector Regression (SVR), and Gaussian Naive Bayes (GaussianNB). Additionally, it provides a web deployment mechanism for the trained models, enabling easy access and utilization.

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 models to classify exoplanets from the raw dataset. Using Python: Sklearn, Joblib, NumPy, Pandas, Matplotlib.

A project focused on anomaly detection within web authentication systems, employing both supervised and unsupervised machine learning techniques to enhance security by pinpointing and analyzing unusual activities.