The objective of this DLM (Deep Learning Model) is to recognize the emotions from speech.

The goal of this project was used advanced preprocessing and feature engineering. Achieved high accuracy with XGBoost and LightGBM. Deployed via a Django web application and visualization was presented using Dash and Plotly.

Ce TP vise à : - La prise en main de la bibliothèque scikit-learn de Python, dédiée à l'apprentissage automatique - Sensibilisation à l'évaluation des modèles appris en classification supervisée. Iris is a dataset introduced in 1936 by Ronald Aylmer Fisher as an example of discriminant analysis.   This set contains 150 examples of criteria obser…

a mini project on iris dataset, choosing the best machine learning model

This is the Data Mining Project for predicting the student's grade before the final and Mid-2 examination. I use Python and Jupyter Notebook for this Project.

Fast-API base StockSeer-API uses different machine learning alogs to forecast closing stock prices.

A modern GUI Based Face Recognition and Emotion Predictor using Machine Learning

This is a Smart Attendance System designed using a pre-trained model called Haar-Cascade Classifier, OpenCV and other various Dependencies to mark the attendance in a smarter way and saves the lecture time.

Heart attack data analysis with python

The project provides information about breast cancer to help doctors predict if a person has it.

This project focuses on developing machine learning models for predicting the presence of diabetes using the logistic regression, support vector machine (SVM) and KNeighborsClassifier algorithms.

Master Decision Trees & Ensembles in Python with this ML notebook! Classification, Regression, Bagging, Boosting, & Tuning. Elevate your ML skills now! 🌲🚀

Advanced Diabetes prediction system with accuracy score train data is 99 and test data 91 using machine learning algorithm

A flask web application that integrates a machine learning model with the capability to make accurate predictions regarding the presence of Parkinson's disease in individuals based on the analysis of their voice recordings

A data-driven project to predict the success of Falcon 9 rocket landings, crucial for cost analysis and competitive strategy in the space industry. Involves data manipulation in Pandas, JSON data processing, and insightful analysis using Python.

Final assignment of the intelligent agents & searching solutions module of the Artificial Intelligence Diploma (DGTIC - UNAM)

Have build a predictive model to determine the likelihood of survival for passengers on the Titanic using data science techniques in Python.

Deep Learning; Machine Learning ; Sklearn ; Seaborn ;Matplotlib; Pycharm

This project aims to study the influence factors of international students' mobility with the case of international students from B&R countries studying in China.