an implementation of a Radial Basis Function Neural Network (RBFNN) for classification problem.

Machine Learning model development for a transport company, the objective is to predict whether an order will arrive on time or not.

End to end implementation and deployment of Machine Learning Car Price Prediction using python, flask, gunicorn, scikit-Learn, etc. on Heroku web application platform.

PySpark Python ML Models

Classifier des mails avec des outils ML

We solve a regression problem in which it consists of calculating the health insurance charge in the United States Where we will break down the project into 5 phases: Exploratory Analysis. Feature Engineering. Selection of the ideal model. Development of the final model. Creation of a web application in streamlit.

Welcome to the world of Speech Emotion Recognition (SER) in Python! This project aims to harness the power of machine learning to detect and classify emotions from spoken language. Whether it's joy, sadness, anger, or any other emotion, our SER model, built using Python libraries and deep learning techniques, can understand and differentiate them.

Image Processing Grades Auto filler with 2 models Graded Sheet Model & Bubble Sheet Model

Implementation & Learning of Compression of Image through use of K-means Clustering Algorithm

A task of sentiment analysis. Classify the Bengali book reviews into positive and negative sentiment.

A Website powered by Machine Learning to find the shortest and safest route dynamically, based on traffic changes for Delhi Metro Services.

Collection of ML models utilized for various problem tasks.

In this project, Jane Street which is a quantitative trading company ,challenged us to build our own quantitative trading model to maximize returns using market data from a major global stock exchange. Next, they’ll test the predictiveness of our models against future market returns.

How does K-pop in the U.S. compare with the popularity of other music genres? Can Spotify’s audio features show what makes certain genres popular? We built a database from Spotify API and Billboard Hot 100 dataset, trained a Random Forest machine learning model, built a dashboard and deployed visualizations to Heroku.

🏆 Machine Learning Estimators

NLP repository with projects like Article Classifiers, Recommender Systems and Text Processing

Machine learning project comparing several algorithms to predict the outcome of shelter animals. Based on the former Kaggle competition: https://www.kaggle.com/c/shelter-animal-outcomes.

The objective of this challenge is to accurately predict the soil moisture level multiple days in advance. This solution will help farmers prepare their irrigation schedules more efficiently