avalon
Andrew-NG-Notes
avalon | Andrew-NG-Notes | |
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2 | 1 | |
169 | 2,282 | |
1.2% | - | |
1.3 | 0.0 | |
about 1 year ago | 3 months ago | |
Jupyter Notebook | Jupyter Notebook | |
GNU General Public License v3.0 only | - |
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avalon
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Using AI to infer depth information from images in Godot 4 .NET 6 using the MiDaS monocular depth model
Good luck with your research! If you want to see a much more comprehensive Godot project doing pretty serious AI research, check out Avalon, which is being developed to train free-acting AI agents in realtime 3D environments.
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Godot Engine Release Management: 4.0 and beyond
If you’re interested there’s a new RL benchmark that was built using Godot (disclaimer I helped make it!)
https://github.com/Avalon-Benchmark/avalon
Andrew-NG-Notes
What are some alternatives?
godot_rl_agents - An Open Source package that allows video game creators, AI researchers and hobbyists the opportunity to learn complex behaviors for their Non Player Characters or agents
Mathematics-for-Machine-Learning-and-Data-Science-Specialization-Coursera - Mathematics for Machine Learning and Data Science Specialization - Coursera - deeplearning.ai - solutions and notes
gdrl - Grokking Deep Reinforcement Learning
machine_learning_complete - A comprehensive machine learning repository containing 30+ notebooks on different concepts, algorithms and techniques.
ml-course - Open Machine Learning course
nn - 🧑🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
fsdl-text-recognizer-2022-labs - Complete deep learning project developed in Full Stack Deep Learning, 2022 edition. Generated automatically from https://github.com/full-stack-deep-learning/fsdl-text-recognizer-2022
DeepNeuralNetworksFromScratch - Different kinds of deep neural networks (DNNs) implemented from scratch using Python and NumPy, with a TensorFlow-like object-oriented API.
strategy-ml-nn - This example shows how to use neural networks for writing a trading system on stocks.
embedml - pytorch like machine learning framework from scratch
Note - Easily implement parallel training and distributed training. Machine learning library. Note.neuralnetwork.tf package include Llama2, Llama3, Gemma, CLIP, ViT, ConvNeXt, BEiT, Swin Transformer, Segformer, etc, these models built with Note are compatible with TensorFlow and can be trained with TensorFlow.