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DeepLearning Note

SoA

mook

  • Stanford CS229: Machine Learning
  • Applied Machine Learning
  • Practical Deep Learning for Coders (2020)
  • Machine Learning with Graphs (Stanford)
  • Probabilistic Machine Learning
  • Introduction to Deep Learning (MIT)
  • Deep Learning: CS 182
  • Deep Unsupervised Learning
  • NYU Deep Learning SP21
  • CS224N: Natural Language Processing with Deep Learning
  • CMU Neural Networks for NLP
  • CS224U: Natural Language Understanding
  • CMU Advanced NLP
  • Multilingual NLP
  • Advanced NLP
  • Deep Learning for Computer Vision
  • Deep Reinforcement Learning
  • Full Stack Deep Learning
  • AMMI Geometric Deep Learning Course (2021)

Pytorch

Christian Perone  - 발표자료: https://speakerdeck.com/perone/pytorch-under-the-hood

  1. Making your RL Projects in 20 Minutes : https://www.edyoda.com/course/1421

  2. Style Transfer, Face Generation using GANs in 20 minutes : https://www.edyoda.com/course/1418

  3. Language and Machine Learning in 20 minutes : https://www.edyoda.com/course/1419

  4. AI Project - Web application for Object Identification : https://www.edyoda.com/course/1185

  5. Dog Breed Prediction : https://www.edyoda.com/course/1336

DL papers

  • ast-SCNN: Fast Semantic Segmentation Network.
  • Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs (https://arxiv.org/pdf/1606.00915.pdf) Source code: https://github.com/vietnguyen91/Deeplab-pytorch
  • Correlational Neural Network. CV, TL, RPL.
  • Reasoning With Neural Tensor Networks for Knowledge Base Completion. NLP, ML. Blog-post
  • Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks. NLP, DL, CQA. Code
  • Common Representation Learning Using Step-based Correlation Multi-Modal CNN. CV, TL, RPL. Code
  • ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs. NLP, AT, DL, STS. Code
  • Combining Neural, Statistical and External Features for Fake News Stance Identification. NLP, IR, DL. Code
  • WIKIQA: A Challenge Dataset for Open-Domain Question Answering. NLP, DL, CQA. Code
  • Siamese Recurrent Architectures for Learning Sentence Similarity. NLP, STS, DL. Code
  • Teaching Machines to Read and Comprehend. NLP, AT, DL. Code
  • Improved Representation Learning for Question Answer Matching. NLP, AT, DL, CQA. Code
  • Map-Reduce for Machine Learning on Multicore]. map-reduce, hadoop, ML.. MR, ML. Code
  • Convolutional Neural Tensor Network Architecture for Community Question Answering. NLP, DL, CQA. Code
  • External features for community question answering. NLP, DL, CQA. Code
  • Language Identification and Disambiguation in Indian Mixed-Script. NLP, IR, ML. Blog-post
  • Construction of a Semi-Automated model for FAQ Retrieval via Short Message Service. NLP, IR, ML. Code

data science tutorial

Tracking Bird Migration Using Python 3 Source Code & Tutorial: https://goo.gl/BS4rQc

Data Science Tutorial Read Here: https://goo.gl/ZPyZBX

Deep Learning (CS 1470)

http://cs.brown.edu/courses/cs1470/index.html

Deep Learning Book

https://www.deeplearningbook.org/ [GitHub] https://github.com/janishar/mit-deep-learning-book-pdf [tutorial] http://www.iro.umontreal.ca/~bengioy/talks/lisbon-mlss-19juillet2015.pdf [videos] https://www.youtube.com/channel/UCF9O8Vj-FEbRDA5DcDGz-Pg/videos

Dive into Deep Learning

https://d2l.ai/ [GitHub] https://github.com/d2l-ai/d2l-en [pdf] https://en.d2l.ai/d2l-en.pdf [STAT 157] http://courses.d2l.ai/berkeley-stat-157/index.html

Neural Network Design

http://hagan.okstate.edu/nnd.html [pdf] http://hagan.okstate.edu/NNDesign.pdf

Neural Networks and Deep Learning

http://neuralnetworksanddeeplearning.com/ [GitHub] https://github.com/mnielsen/neural-networks-and-deep-learning [pdf] http://static.latexstudio.net/article/2018/0912/neuralnetworksanddeeplearning.pdf [solutions] https://github.com/reachtarunhere/nndl/blob/master/2016-11-22-ch1-sigmoid-2.md

Theories of Deep Learning (STATS 385)

https://stats385.github.io/ [videos] https://www.researchgate.net/project/Theories-of-Deep-Learning

Theoretical Principles for Deep Learning (IFT 6085)

http://mitliagkas.github.io/ift6085-dl-theory-class-2019/

A collection of links of videos(youtube) by course

https://github.com/kmario23/deep-learning-drizzle/blob/master/README.md

A collection of tutorial Jupyter notebooks

https://github.com/jupyter/jupyter/wiki/A-gallery-of-interesting-Jupyter-Notebooks

the matrix calculus

https://explained.ai/matrix-calculus/index.html

etc

https://fleuret.org/ee559/ http://deep-learning-phd-course-2018-xb.s3-website-ap-southeast-1.amazonaws.com/ https://www.fast.ai/

refe. https://www.reddit.com/r/MachineLearning/comments/anrams/d_sharing_my_personal_resource_list_for_deep/

Annotation detect

  • Anomaly Detection with Generative Adversarial Networks for Multivariate Time Series

Tensorflow

The TenSorFlow is an Open Soruce Software Library for Machine Intellience. This repository are many jupyter note-pad like TesroFlow turorials, step books, and others.

DeepMind's WaveNet

DeepVoice

Deep Voice: Real-Time Neural Text-to-Speech for Production

  • Sercan O. Arik, Mike Chrzanowski, Adam Coates, Gregory Diamos, Andrew Gibiansky, Yongguo Kang, Xian Li, John Miller, Jonathan Raiman, Shubho Sengupta, Mohammad Shoeybi
  • [paper]
  • [Ref.code

Very simple TensorFlow examples

GAN

Style-based GAN

Pytorch a2c

  • Advantage Actor Critic (A2C), a synchronous deterministic version of A3C
    • Volodymyr Mnih1
    • Adria Puigdomenech Badia1
    • Mehdi Mirza1,2
    • Alex Graves1
    • Tim Harley1
    • Timothy P. Lillicrap1
    • David Silver1
    • Koray Kavukcuoglu1
  • code

Sequence to Sequence -- Video to Text

  • Subhashini Venugopalan, Marcus Rohrbach, Jeff Donahue, Raymond Mooney, Trevor Darrell, Kate Saenko, arxiv, 2015
  • [code]
  • [paper]

Sequence to Sequence -- chatbot

  • Oriol Vinyals, Quoc V. Le, arxiv, 2015
  • [code]
  • [paper]

Show and Tell: A Neural Image Caption Generator

  • Oriol Vinyals, Alexander Toshev, Samy Bengio, Dumitru Erhan, arxiv, 2015
  • [code]
  • [paper]

Show, Attend and Tell: Neural Image Caption Generation with Visual Attention

  • Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron Courville, Ruslan Salakhutdinov, Richard Zemel, Yoshua Bengio, ICLR, 2014
  • [code]
  • [paper]

Learning Deep Features for Discriminative Localization

  • Bolei Zhou, Aditya Khosla, Agata Lapedriza, Aude Oliva, Antonio Torralba, CVPR, 2016
  • [code]
  • [paper]

Deep Visual Analogy-Making

  • Scott Reed, Yi Zhang, Yuting Zhang, Honglak Lee, NIPS, 2015
  • [code]
  • [paper]

Deep Convolutional Generative Adversarial Networks

  • Alec Radford, Luke Metz, Soumith Chintala, arxiv, 2015
  • [code]
  • [paper]

End-To-End Memory Networks

  • Sainbayar Sukhbaatar, Arthur Szlam, Jason Weston, Rob Fergus, NIPS, 2015
  • [code]
  • [paper]

Character-Aware Neural Language Models

  • Yoon Kim, Yacine Jernite, David Sontag, Alexander M. Rush, AAAI, 2016
  • [code]
  • [paper]

Deep Reinforcement Learning

Human-level control through deep reinforcement learning

  • Volodymyr Mnih, et al, 2014
  • [code1], not trained on atari
  • [code2]
  • [paper]

Deep Reinforcement Learning with Double Q-learning

  • Hado van Hasselt, Arthur Guez, David Silver, 2015
  • [code]
  • [paper]

Using Deep Q-Network to Learn How To Play Flappy Bird

Semi-Supervised Learning with Ladder Network

Convolutional Neural Networks for Sentence Classification

Black-Box Adversarial Perturbations

Implementation of Simple Black-Box Adversarial Perturbations for Deep Networks in Keras fork from link

  • python cifar100.py to train a basic CNN for cifar100 and save that file.
  • python find_better.py <model> to go through cifar100 test dataset and find a good image (as defined in the paper).
  • python per.py <KERAS_MODEL> <IMAGE_in_NUMPY> : currently works for cifar images only.

Deep Residual Learning for Image Recognition

colornet - Neural Network to colorize grayscale images

DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients

  • Shuchang Zhou, Zekun Ni, Xinyu Zhou, He Wen, Yuxin Wu, Yuheng Zou, 2016
  • [code]
  • [paper]

A Neural Algorithm of Artistic Style

콘크리트 구조물 균열 탐지 및 분석

csv ttols

https://github.com/eBay/tsv-utils.git

Sequence Generative Adversarial Networks

Reference

  • CV | Computer Vision
  • TL | Transfer Learning
  • RPL | Representation Learning
  • CQA | Community Question Answering
  • STS | Sentence Text Similarity
  • IR | Information Retrieval
  • AT | Attention
  • MR | Map Reduce
  • ASR | Acoustic Scene Recognition
  • DL | Deep Learning
  • NLP | Natural Language Processing
  • ML | Machine Learning.

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