📈 Quant Market Predictor is a Python tool designed to predict stock prices from the NASDAQ

Building a predictive model to predict views of Ted Talks in YouTube from dataset of past events using Machine Learning models

🐾 A lightweight & extensible library to create complex multi-model and multi-modal pipelines, including ``Ensembles`` and ``Meta-Models``

Guidelines for the course "fundamentals of machine learning"

Credit Card Fraud Detection Using Machine Learning

Practical tasks that were performed during the course Specialization DS

Problem to solve: Predict if a candidate would be hired based on specific characteristics; what are the most important features a candidate must have to have higher possibilities of getting the job?

Repo hosting the notebooks for the assignments of the fall 21 "Neural Networks and Intelligent Systems" course @ NTUA

This project uses machine learning to predict and analyze employee attrition in Company.By developing three predictive models,it identifies key factors influencing turnover,providing actionable insights to mitigate attrition challenges.The analysis focuses on enhancing job satisfaction,work-life balance and career growth opportunities.

With imbalanced observed data, a search for the best model is conducted. The bank is seeing its customers leave. Wondering if there are patterns to their decision to exit, the bank wishes to anticipate for this trend. When the positive class is the minority in an imbalanced dataset, a model need to be trained for robustness.

Diabetes prediction

Machine Learning projects

Code Repository for Perceptron Learning Algorithm

Forecasting hourly bike rental demand by combining historical usage patterns with weather data using Linear Regression Algorithm.

It's a python program to Visualise the Covid-19 Situation and Predict the Covid Cases in Upcoming Days

UOC University - Applied Data Science Engineering - Fundamentals of Data Science - PEC_7 || Data preprocessing in Python. Libraries: Scikit-learn and Pandas. ||

🚢 Ce projet utilise les données du Titanic pour prédire la survie des passagers en fonction de caractéristiques comme l'âge, le sexe et la classe. À travers des modèles de machine learning et des visualisations, il explore les facteurs clés de survie dans l'un des naufrages les plus célèbres de l'histoire.