This tutorial aims to learn the basics of deep learning by hands, and master the basics through combination of lectures and exercises

Overview

2021-Deep-learning

This tutorial aims to learn the basics of deep learning by hands, and master the basics through combination of paper and exercises. The first folder is named Paper. The papers I have read before the graduate level have not been well organized and retained. I want to update the classic papers on classification, detection, and segmentation from 2012 to the present(Theory and realization). The second folder is named Demo that contains practical and theoretical tutorials for hands-on deep learning. The third folder is the install tutorial series, which contains the installation methods of the most popular deep learning framework Pytorch.

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Designing a Practical Degradation Model for Deep Blind Image Super-Resolution (ICCV, 2021) (PyTorch) - We released the training code!

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CVPR2021 Workshop - HDRUNet: Single Image HDR Reconstruction with Denoising and Dequantization.

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Stochastic gradient descent with model building

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Nvidia Semantic Segmentation monorepo

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NEO: Non Equilibrium Sampling on the orbit of a deterministic transform

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AniGAN: Style-Guided Generative Adversarial Networks for Unsupervised Anime Face Generation

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As much as this series is to educate aspiring computer programmers and data scientists of all ages and all backgrounds, it is also a reminder to mysel

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USAD - UnSupervised Anomaly Detection on multivariate time series

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Full Stack Deep Learning Labs

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Animation of solving the traveling salesman problem to optimality using mixed-integer programming and iteratively eliminating sub tours

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Lux AI environment interface for RLlib multi-agents

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Underwater image enhancement

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This repository contains the code for the paper in EMNLP 2021: "HRKD: Hierarchical Relational Knowledge Distillation for Cross-domain Language Model Compression".

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Chenhe Dong 2 Mar 24, 2022