Movie Revenue Prediction System predicts the revenue of a movie with 14 parameters: name, rating, genre, year, released, score, votes, director, writer, star, country, budget, company and runtime using gradient boosting______________________________ Training Accuracy: 91.58%____________ Testing Accuracy: 82.42%.

Implementation of ML algorithms for FlipKart Product Category Classification based on the product's description and other features.

This is a portotype of GitHub recommender system.

Some dimensionality reduction and clustering examples using sklearn library

Real time face detection and recognition integrating with CCTV

DE and DA samples

Kaggle fun house

Analyzed a 23-feature dataset, targeting 'RainTomorrow' for weather insights. Conducted thorough data gathering, preprocessing, and feature selection. Evaluated diverse models (Logistic Regression, Random Forest, Decision Trees, K-means, K-nearest neighbors, Hierarchical clustering) and employed technical metrics for in-depth performance analysis.

This is a regression problem to predict california housing prices.

scikit-learn Library (sk-learn) / Biblioteca scikit-learn (sk-learn)

This project demonstrates various machine learning techniques for classifying handwritten digits from the MNIST dataset. It covers data preprocessing, model training, evaluation, and advanced classification strategies.

A Random Forest Approach to Estimate Rainfall

Regression Analysis of oceanographic data to find the relationship between the temperature and the salinity of water.

Projet réalisé pour INSPIRE d'Article 1, mise en place d'algorithme de modération.

Testing AdaBoost and other functionality of sklearn library on different datasets.

Face recognition using PCA and K-NN

Spam Classifier using Naive Bayesian Method

An interactive stock dashboard, enabling users to input stock codes, select dates, and visualize trends, indicators, and forecasts. Utilized yfinance for historical data and integrated SVR model for predictive analysis, showcasing interactive charts and forecasts.