gdrl
conformal_classification
gdrl | conformal_classification | |
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1 | 2 | |
747 | 211 | |
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10.0 | 0.0 | |
about 2 years ago | over 1 year ago | |
Jupyter Notebook | Jupyter Notebook | |
BSD 3-clause "New" or "Revised" License | MIT License |
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gdrl
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How to proceed further? (Learning RL)
I would recommend looking at Grokking Deep RL if you are looking for some hands on DRL practice in python without starting completely from scratch. You can find some of the jupyter notebooks here.
conformal_classification
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[P] 🚀 AWS launches Fortuna, an open-source library for Uncertainty Quantification
What is the best end-to-end example showing it? https://github.com/awslabs/fortuna/blob/main/examples/mnist_classification.ipynb ? It would be nice to have some visual explainer, as in https://github.com/aangelopoulos/conformal_classification .
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[R] Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification - Link to a free online lecture by the author in comments
​Uncertainty Sets for Image Classifiers using Conformal Prediction https://arxiv.org/abs/2009.14193 https://github.com/aangelopoulos/conformal_classification
What are some alternatives?
deep-rl-class - This repo contains the syllabus of the Hugging Face Deep Reinforcement Learning Course.
learnopencv - Learn OpenCV : C++ and Python Examples
World4AI - World4AI is an educational resource for AI.
AI-For-Beginners - 12 Weeks, 24 Lessons, AI for All!
Andrew-NG-Notes - This is Andrew NG Coursera Handwritten Notes.
glasses - High-quality Neural Networks for Computer Vision 😎
baselines - OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
DeepLearning - Contains all my works, references for deep learning
Practical_RL - A course in reinforcement learning in the wild
geomstats - Computations and statistics on manifolds with geometric structures.
Reinforcement-Learning - Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning
Deep-Learning-Experiments - Videos, notes and experiments to understand deep learning