Sentiment Analysis of Film Review at IMDB using Linear Support Vector Classification

Machine learning models that predict whether the customers are happy or not based on survey responses

This project implements NLP and Classification models for Spam SMS detection

Sentiment analysis of kinopoisk (https://www.kinopoisk.ru/) reviews. For analysis i used: classification methods (random forest, svc, k-neighbors) neural networks (lstm, mlp).

🏆 Top 10 @ TensorFlow Group ML Olympiad 2024 - Developing a model to classify each customer opinon into several Likert scale with data gathered directly from Google Reviews

Over the years, the company has collected basic bank details and gathered a lot of credit-related information. The management wants to build an intelligent system to segregate the people into credit score brackets to reduce the manual efforts.. You are hired as a data scientist to build a machine learning model that can classify the credit score.

This model predicts the Diabetes by using the Logistic Regression or SVC with using the Flask app

Classification Machine Learning project

Predicting the risk of a person developing the coronary heart disease in 10 years using Machine Learning models.

This python project explains how to implement sentiment analysis using machine learning (SVM) on amazon Alexa reviews dataset.

This is in regard to algorithmic trading bot with the use of machine learning to predict potential returns and actual returns.

Prevendo a postura usando traços de personalidade

Using past Sport (Cricket) data to predict next win for Team India, in any format of the cricket.

Text classification with Machine Learning and Mealpy

GridSearchCV For Model optimization

Predict upper case alphabet using SVM model

This project demonstrates how to create a sentiment analysis and machine learning model on the IMDB dataset

ML model to predict whether the person has Parkinson's Disease.

This project involves collecting Reddit submission posts from r/LiverpoolFC and r/Everton using Pushshift's API, and employing Natural Language Processing (NLP) to train models that can accurately determine the origin of the posts, differentiating between the two football club subreddits.

I participated in the Titanic ML competition where I used machine learning to create a model to predict which passengers survived the Titanic shipwreck.