This is a collection of my submissions to the ongoing Kaggle Playground Series!

This website provides a platform for users to predict their likelihood of developing diabetes based on various factors.

This project is dedicated to the analysis and processing of data related to electric vehicles. It involves thorough examination, cleaning, and visualization of the dataset to extract valuable insights. The primary focus is on understanding trends in electric vehicle usage and characteristics.

Data search & enrichment library for Machine Learning → Easily find and add relevant features to your ML & AI pipeline from hundreds of public and premium external data sources, including open & commercial LLMs

Web demo Machine Learning Models from kaggle projects

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

Different projects to discover Data Science

PyTorch extensions for fast R&D prototyping and Kaggle farming

Kaggle Notebooks

This repository contains my code for training and runnning a machine learning model, for classifying images of the American Sign Language (ASL) alphabet. The model was architected and trained using a Google's TensorFlow library.

A set of resources around Neo4J ninjas program

Daily consolidated and enriched snapshots of endoflife.date

数据挖掘、计算机视觉、自然语言处理、推荐系统竞赛知识、代码、思路

My Kaggle Github Repository

This web application provides a comprehensive platform for testing and interacting with various AI agents developed for the ConnectX game. Built with a React frontend and a Python Flask backend, this platform offers a visually engaging interface that allows users to easily interact with and evaluate the performance of different game AI agents.

From a selection of data from the Roboflow file https://universe.roboflow.com/landy-aw2jb/fracture-ov5p1/dataset/1, which represents a reduced but homogeneous version of that file, a model is obtained using an adaptation of the project https://www.kaggle.com/code/nyachhyonjinu/yolov3-test instead any yolo model

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

Stable-Diffusion-WebUI. One simple notebook for two environments: Colab (Pro|Free) / Kaggle.

A machine learning model implemented in Rust 🦀 + Burn 🔥 for the LEAP - Atmospheric Physics using AI (ClimSim) Kaggle challenge

Collection of my Kaggle Notebooks