Machine Learning · GitHub

CatBoost a fast, scalable, high performance Gradient Boosting on Decision Trees library. Golang using Cgo for blazing fast inference CatBoost Model 🚀

• CatBoostRegressor ✅
• CatBoostClassifier ✅

This repository contains structured notes, implementations, and projects based on a complete Natural Language Processing (NLP) course.

CURL: Contrastive Unsupervised Representation Learning for Sample-Efficient Reinforcement Learning

A pytorch implementation of the vector quantized variational autoencoder (https://arxiv.org/abs/1711.00937)

ROS package for dynamic obstacle avoidance for ground robots trained with deep RL

[NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning

Confidential AI deployment with secure enclaves :lock:

MIT IAP short course: Matrix Calculus for Machine Learning and Beyond

Asynchronous Methods for Deep Reinforcement Learning

nessai: Nested Sampling with Artificial Intelligence

[ICIP'24 Lecture Presentation] Official implementation of "CST-YOLO: A Novel Method for Blood Cell Detection Based on Improved YOLOv7 and CNN-Swin Transformer".

[MICCAI'23] Official implementation of "RCS-YOLO: A Fast and High-Accuracy Object Detector for Brain Tumor Detection".

Official PyTorch implementation of "Expressive Whole-Body 3D Gaussian Avatar", ECCV 2024.

Official PyTorch implementation of "I2L-MeshNet: Image-to-Lixel Prediction Network for Accurate 3D Human Pose and Mesh Estimation from a Single RGB Image", ECCV 2020

A machine learning course using Python, Jupyter Notebooks, and OpenML

machine learning for artists