Stars
An educational AI robot based on NVIDIA Jetson Nano.
A collection of infrastructure and tools for research in neural network interpretability.
Deep Replay - Generate visualizations as in my "Hyper-parameters in Action!" series!
Visual analysis and diagnostic tools to facilitate machine learning model selection.
TensorFlow for NVIDIA Jetson, also include patch and script for building.
GPUProfiler - Understand your application and workflow resource requirements
FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.
Deep Learning Tutorial for Kaggle Ultrasound Nerve Segmentation competition, using Keras
TensorFlow-based implementation of "ICNet for Real-Time Semantic Segmentation on High-Resolution Images".
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
🏭 Collaboratively build, visualize, and design neural nets in browser
openpilot is an operating system for robotics. Currently, it upgrades the driver assistance system on 300+ supported cars.
Tiny YOLO for iOS implemented using CoreML but also using the new MPS graph API.
List of all the lessons learned, best practices, and links from my time studying machine learning
A modern development environment for deep learning
Visualizations for machine learning datasets
Euclid object labeller for frictionless object detection training purposes in Machine learning frameworks (KITTI, YOLO)
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
The Udacity open source self-driving car project
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
Improving Convolutional Networks via Attention Transfer (ICLR 2017)
PyTorch Tutorial for Deep Learning Researchers
Implementation of the approach described in the paper "Recurrent Instance Segmentation" https://arxiv.org/abs/1511.08250.
Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.
Repository for all the tutorials and codes shared at cv-tricks.com