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PyTorch deep learning projects made easy.
Machine Learning University: Accelerated Tabular Data Class
Reinforcement learning tutorials
[CVPR 2025 - Spotlight] Official PyTorch implementation of MAtCha Gaussians: Atlas of Charts for High-Quality Geometry and Photorealism From Sparse Views
A simple implementation of GradCAM (Gradient-weighted Class Activation Mapping) using PyTorch and OpenCV.
We are developing an intelligent system (EcoData) for automating research on plant bioindicators. The system helps automate measurements, research, and data processing that are necessary to assess …
PyTorch implementations of deep reinforcement learning algorithms and environments
Implementations from the free course Deep Reinforcement Learning with Tensorflow and PyTorch
🧠💬 Articles I wrote about machine learning, archived from MachineCurve.com.
Understanding Deep Learning - Simon J.D. Prince
This repository includes an implementation of reinforcement learning algorithms. The notebook provides a step-by-step guide on how to train and test reinforcement learning models on various environ…
About The dataset was recorded on the Husky robotics platform on the university campus and consists of 5 tracks recorded at different times of day (day/dusk/night) and different seasons (winter/spr…
ETL, Analytics, Versioning for Unstructured Data
A resource for learning about Machine learning & Deep Learning
Text and supporting code for Think Stats, 2nd Edition
A PyTorch-based Python library with UNet architecture and multiple backbones for Image Semantic Segmentation.
clustering of image using python without using kmeans and dbscan import modules developing own code
Roadmap to becoming an Artificial Intelligence Expert in 2022
The "Python Machine Learning (2nd edition)" book code repository and info resource
数式の逆ポーランド記法コンバート。および逆ポーランド記法の演算。
A deep CNN model trained to recognize and categorize shoes from digital catalogs (of e-commerce companies), image data contains 5 different viewing angles for same shoe image.
All Algorithms implemented in Python