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.

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%.

Some dimensionality reduction and clustering examples using sklearn library

DE and DA samples

Real time face detection and recognition integrating with CCTV

This is a regression problem to predict california housing prices.

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.

A Random Forest Approach to Estimate Rainfall

Face recognition using PCA and K-NN

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

Spam Classifier using Naive Bayesian Method

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

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

Aim of the problem is to find the health insurance cost incured by Individuals based on thier age, gender, BMI, number of children, smoking habit and geo-location.

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.