Python Scripts and Jupyter Notebooks

Kaggle Kernels (Python, R, Jupyter Notebooks)

Notebooks for training the classifier of YASA sleep staging

The complete code and notebooks used for the ACM Recommender Systems Challenge 2019

Cambridge UK temperature forecast python notebooks

预测rossmann1115家商店未来的销售额

Bunch of notebooks collection from Kaggle competitions.

Comparison of methods for predicting electricity consumption of a large non-residential building.

Machine Learning Notebooks

🦠 Breast cancer survival prediction (notebook + streamlit)

Notebooks exploring strengths and weaknesses of GBM based classifiers

This repository contains all the notebooks, resources, and documentation used to develop and evaluate models for the Automated Essay Scoring (AES) Kaggle competition. The project aims to build an open-source solution for automated essay evaluation to support educators and provide timely feedback to students.

This repository contains various machine learning regression models implemented in Python. Each sub-directory represents a different regression algorithm, complete with its dataset, trained model, and a Jupyter Notebook demonstrating the implementation.

The notebook shows how machine learning tools and algorithms (scikit-learn, XGBoost, LightGBM) work in practice.

Our team's work during the Dataverse 2.0 competition that was hosted by ENSA Khouribga during the 20th and 21st of November 2023.

ML-powered fraud detection for UPI transactions | 87% F1-Score | XGBoost + Flask | Real-time predictions | Interactive notebooks

❤️ Predict heart disease risk using classic machine learning techniques with this Jupyter notebook project, featuring data exploration and model building.

Car Price Prediction – Machine learning project for estimating car prices based on technical specifications and market data. The goal is to achieve an RMSE below 2500 by comparing multiple models (Linear Regression, Random Forest, LightGBM) and analyzing training vs. prediction time.

The complete code and notebooks used for the ACM Recommender Systems Challenge 2021 by our team Trial&Error at Politecnico di Milano

This project analyzes phone usage patterns in India and predicts the primary use of mobile devices based on various features. The notebook covers data preprocessing, exploratory data analysis (EDA), and model training using multiple classification algorithms.