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Title: GitHub - androidcodehub/Great-Deep-Learning-Tutorials: A Great Collection of Deep Learning Tutorials and Repositories

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https://github.com/androidcodehub/Great-Deep-Learning-Tutorials#great-deep-learning-tutorials
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Browse state-of-the-art Deep Learning based Papers with their associated codeshttps://paperswithcode.com/sota
Deep-Learning-Roadmaphttps://github.com/astorfi/Deep-Learning-Roadmap
DeepLizardhttps://deeplizard.com/
Excellent Bloghttps://lilianweng.github.io/lil-log/
The 6 most useful Machine Learning projects of the past year (2018)https://towardsdatascience.com/the-10-most-useful-machine-learning-projects-of-the-past-year-2018-5378bbd4919f
ResNet Reviewhttps://towardsdatascience.com/review-resnet-winner-of-ilsvrc-2015-image-classification-localization-detection-e39402bfa5d8
https://github.com/androidcodehub/Great-Deep-Learning-Tutorials#semantic-segmentation
Simple Guide to Semantic Segmentationhttps://medium.com/beyondminds/a-simple-guide-to-semantic-segmentation-effcf83e7e54
https://github.com/androidcodehub/Great-Deep-Learning-Tutorials#model-visualization
CNN Visualizationshttps://github.com/utkuozbulak/pytorch-cnn-visualizations
Netron - GitHubhttps://github.com/lutzroeder/netron
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Understanding CNNhttp://cs231n.github.io/understanding-cnn/
https://github.com/androidcodehub/Great-Deep-Learning-Tutorials#quantization--distillation-of-deep-learning-models
Quantizationhttps://nervanasystems.github.io/distiller/quantization/
Neural Network Distillerhttps://github.com/NervanaSystems/distiller/
Dynamic Quantization in PyTorchhttps://pytorch.org/tutorials/advanced/dynamic_quantization_tutorial.html
Static Quantization in PyTorchhttps://pytorch.org/tutorials/advanced/static_quantization_tutorial.html
Intel(R) Math Kernel Library - Intel MKL-DNNhttps://github.com/intel/mkl-dnn
Intel MKL-Dnnhttps://01.org/mkl-dnn
ONNX Float32 to Float16https://github.com/onnx/onnx-docker/blob/master/onnx-ecosystem/converter_scripts/float32_float16_onnx.ipynb
Neural Network Quantization Introductionhttps://jackwish.net/neural-network-quantization-introduction.html
https://github.com/androidcodehub/Great-Deep-Learning-Tutorials#3d-image-classification
3D MNISThttps://medium.com/shashwats-blog/3d-mnist-b922a3d07334
3D CNN Images with Tensorflowhttps://github.com/jibikbam/CNN-3D-images-Tensorflow
Point Cloud Library (PCL)https://github.com/PointCloudLibrary/pcl
https://github.com/androidcodehub/Great-Deep-Learning-Tutorials#learning-to-hash--general-hashing--fast-searching-methods
Finding similar images using Deep learning and Locality Sensitive Hashinghttps://towardsdatascience.com/finding-similar-images-using-deep-learning-and-locality-sensitive-hashing-9528afee02f5
Image similarity using Triplet Losshttps://towardsdatascience.com/image-similarity-using-triplet-loss-3744c0f67973
Finding duplicate images made easy!https://github.com/idealo/imagededup
https://github.com/androidcodehub/Great-Deep-Learning-Tutorials#gans
Generate Anime Style Face Using DCGAN and Explore Its Latent Feature Representationhttps://towardsdatascience.com/generate-anime-style-face-using-dcgan-and-explore-its-latent-feature-representation-ae0e905f3974
https://github.com/androidcodehub/Great-Deep-Learning-Tutorials#few-shot-learning
Advances in few-shot learninghttps://towardsdatascience.com/advances-in-few-shot-learning-a-guided-tour-36bc10a68b77
Advances in few-shot learning: reproducing results in PyTorchhttps://towardsdatascience.com/advances-in-few-shot-learning-reproducing-results-in-pytorch-aba70dee541d
https://github.com/androidcodehub/Great-Deep-Learning-Tutorials#deep-learning-for-data-science
Introduction to Anomaly Detection in Pythonhttps://blog.floydhub.com/introduction-to-anomaly-detection-in-python/
https://github.com/androidcodehub/Great-Deep-Learning-Tutorials#deep-learning-recommendation-model
Deep Learning Recommendation Model for Personalization and Recommendation Systems - DLRMhttps://github.com/facebookresearch/dlrm
DLRM: An advanced, open source deep learning recommendation modelhttps://ai.facebook.com/blog/dlrm-an-advanced-open-source-deep-learning-recommendation-model/
Neural Recommendation Algorithmshttps://towardsdatascience.com/recotour-ii-neural-recommendation-algorithms-49733938d56e
https://github.com/androidcodehub/Great-Deep-Learning-Tutorials#nlp
Great NLP Postshttp://jalammar.github.io/
Ten trends in Deep learning NLPhttps://blog.floydhub.com/ten-trends-in-deep-learning-nlp/
A Gentle Introduction to Text Summarization in Machine Learninghttps://blog.floydhub.com/gentle-introduction-to-text-summarization-in-machine-learning/
Attention in RNNshttps://medium.com/datadriveninvestor/attention-in-rnns-321fbcd64f05
BERT - TensorFlowhttps://github.com/google-research/bert
Understanding XLNethttps://www.borealisai.com/en/blog/understanding-xlnet/
XLNet - TensorFlowhttps://github.com/zihangdai/xlnet
XLM (PyTorch implementation of Cross-lingual Language Model Pretraining)https://github.com/facebookresearch/XLM
Pretrained PyTorch models for BERThttps://github.com/huggingface/pytorch-pretrained-BERT
Library of state-of-the-art pretrained models for NLPhttps://github.com/huggingface/pytorch-transformers#quick-tour
DistilBERThttps://medium.com/huggingface/distilbert-8cf3380435b5
PyTorch Hub - BERThttps://pytorch.org/hub/huggingface_pytorch-pretrained-bert_bert/
A Simple Guide On Using BERT for Binary Text Classificationhttps://medium.com/swlh/a-simple-guide-on-using-bert-for-text-classification-bbf041ac8d04
Core ML 3 implementation of BERT for Question answeringhttps://github.com/huggingface/swift-coreml-transformers
https://github.com/androidcodehub/Great-Deep-Learning-Tutorials#text-representation
Beyond Word Embeddings Part 1https://towardsdatascience.com/beyond-word-embeddings-part-1-an-overview-of-neural-nlp-milestones-82b97a47977f
Beyond Word Embeddings Part 2https://towardsdatascience.com/beyond-word-embeddings-part-2-word-vectors-nlp-modeling-from-bow-to-bert-4ebd4711d0ec
Learning Word Embeddinghttps://lilianweng.github.io/lil-log/2017/10/15/learning-word-embedding.html
Introduction to Word Embedding and Word2Vechttps://towardsdatascience.com/introduction-to-word-embedding-and-word2vec-652d0c2060fa
Word Embeddinghttps://medium.com/data-science-group-iitr/word-embedding-2d05d270b285
Understanding Word Embeddingshttps://hackernoon.com/understanding-word-embeddings-a9ff830403ce
Introduction to Word Vectorshttps://medium.com/@jayeshbahire/introduction-to-word-vectors-ea1d4e4b84bf
Word2vec Made Easyhttps://towardsdatascience.com/word2vec-made-easy-139a31a4b8ae
What is GloVe? Part Ihttps://towardsdatascience.com/emnlp-what-is-glove-part-i-3b6ce6a7f970
What is GloVe? Part IIhttps://towardsdatascience.com/emnlp-what-is-glove-part-ii-9e5ad227ee0
What is GloVe? Part IIIhttps://towardsdatascience.com/emnlp-what-is-glove-part-iii-c6090bed114
What is GloVe? Part IVhttps://towardsdatascience.com/emnlp-what-is-glove-part-iv-e605a4c407c8
What is GloVe? Part Vhttps://towardsdatascience.com/emnlp-what-is-glove-part-v-fa888272c290
https://github.com/androidcodehub/Great-Deep-Learning-Tutorials#rnn-lstm-and-gru
Understanding LSTM Networkshttps://colah.github.io/posts/2015-08-Understanding-LSTMs/
Illustrated Guide to LSTM’s and GRU’shttps://towardsdatascience.com/illustrated-guide-to-lstms-and-gru-s-a-step-by-step-explanation-44e9eb85bf21
Animated RNN, LSTM and GRUhttps://towardsdatascience.com/animated-rnn-lstm-and-gru-ef124d06cf45
Recurrent Neural Networks and LSTM explainedhttps://medium.com/@purnasaigudikandula/recurrent-neural-networks-and-lstm-explained-7f51c7f6bbb9
Long Short-Term Memory (LSTM): Concepthttps://medium.com/@kangeugine/long-short-term-memory-lstm-concept-cb3283934359
Understanding architecture of LSTM cell from scratchhttps://hackernoon.com/understanding-architecture-of-lstm-cell-from-scratch-with-code-8da40f0b71f4
Basic understanding of LSTMhttps://blog.goodaudience.com/basic-understanding-of-lstm-539f3b013f1e
https://github.com/androidcodehub/Great-Deep-Learning-Tutorials#transformers
How Transformers Workhttps://towardsdatascience.com/transformers-141e32e69591
The Illustrated Transformerhttp://jalammar.github.io/illustrated-transformer/
What is a Transformer?https://medium.com/inside-machine-learning/what-is-a-transformer-d07dd1fbec04
Transformer: A Novel Neural Network Architecture for Language Understandinghttps://ai.googleblog.com/2017/08/transformer-novel-neural-network.html
How do Transformers Work in NLP?https://www.analyticsvidhya.com/blog/2019/06/understanding-transformers-nlp-state-of-the-art-models/
BERT for Dummieshttps://towardsdatascience.com/bert-for-dummies-step-by-step-tutorial-fb90890ffe03
https://github.com/androidcodehub/Great-Deep-Learning-Tutorials#attention-mechanism
Attention Mechanismhttps://blog.floydhub.com/attention-mechanism/
Visualizing A Neural Machine Translation Model - Attention Mechanismhttps://jalammar.github.io/visualizing-neural-machine-translation-mechanics-of-seq2seq-models-with-attention/
https://github.com/androidcodehub/Great-Deep-Learning-Tutorials#nlp-programming-notes
100 Times Faster Natural Language Processing in Pythonhttps://medium.com/huggingface/100-times-faster-natural-language-processing-in-python-ee32033bdced
Multi-label Text Classification using BERThttps://medium.com/huggingface/multi-label-text-classification-using-bert-the-mighty-transformer-69714fa3fb3d
Learning Meaning in Natural Language Processinghttps://medium.com/huggingface/learning-meaning-in-natural-language-processing-the-semantics-mega-thread-9c0332dfe28e
Train and Deploy the Mighty Transformer NLP models using FastBert and AWS SageMakerhttps://medium.com/@kaushaltrivedi/train-and-deploy-mighty-transformer-nlp-models-using-fastbert-and-aws-sagemaker-cc4303c51cf3
https://github.com/androidcodehub/Great-Deep-Learning-Tutorials#video-understanding
Holistic Video Understanding Challengehttps://holistic-video-understanding.github.io/workshops/iccv2019.html
Holistic Video Understanding Datasethttps://github.com/holistic-video-understanding/Mini-HVU
Holistic Large Scale Video Understanding - Tutorialhttps://towardsdatascience.com/holistic-large-scale-video-understanding-c423701b777a
https://github.com/androidcodehub/Great-Deep-Learning-Tutorials#spoken-language-processing-speech-processing
Audio Classificationhttps://towardsdatascience.com/audio-classification-using-fastai-and-on-the-fly-frequency-transforms-4dbe1b540f89
Building a Dead Simple Word Recognition Engine Using Convnethttps://blog.manash.me/building-a-dead-simple-word-recognition-engine-using-convnet-in-keras-25e72c19c12b
Identifying the Genre of a Song with Neural Networkshttps://medium.com/@navdeepsingh_2336/identifying-the-genre-of-a-song-with-neural-networks-851db89c42f0
Modelling audio signal using visual featureshttps://raghavgoyal14.github.io/2018/04/12/audio-via-vid-features.html
https://github.com/androidcodehub/Great-Deep-Learning-Tutorials#deep-reasoning
What’s Next For AI? Enter: Deep Reasoninghttps://towardsdatascience.com/whats-next-for-ai-enter-deep-reasoning-fae8b131962a
Deep Learning approaches to understand Human Reasoninghttps://towardsdatascience.com/deep-learning-approaches-to-understand-human-reasoning-46f1805d454d
https://github.com/androidcodehub/Great-Deep-Learning-Tutorials#object-detection
Object Detection for Dummies Part 1https://lilianweng.github.io/lil-log/2017/10/29/object-recognition-for-dummies-part-1.html
Object Detection for Dummies Part 2https://lilianweng.github.io/lil-log/2017/12/15/object-recognition-for-dummies-part-2.html
Object Detection for Dummies Part 3https://lilianweng.github.io/lil-log/2017/12/31/object-recognition-for-dummies-part-3.html
Object Detection for Dummies Part 4https://lilianweng.github.io/lil-log/2018/12/27/object-detection-part-4.html
Open MMLab Detection Toolbox and Benchmarkhttps://github.com/open-mmlab/mmdetection
https://github.com/androidcodehub/Great-Deep-Learning-Tutorials#visual-question-answering-vqa
Vanilla VQAhttps://medium.com/ai2-blog/vanilla-vqa-adcaaaa94336
https://github.com/androidcodehub/Great-Deep-Learning-Tutorials#license-plate-detection-and-recognition
ALPR in Unscontrained Scenarioshttps://github.com/sergiomsilva/alpr-unconstrained
ALPR in Unscontrained Scenarios - Project Pagehttp://sergiomsilva.com/pubs/alpr-unconstrained/
https://github.com/androidcodehub/Great-Deep-Learning-Tutorials#deep-reinforcement-learning-great-courses--tutorials
A Free course in Deep Reinforcement Learning from beginner to experthttps://simoninithomas.github.io/Deep_reinforcement_learning_Course/
Deep Reinforcement Learning Algorithms with PyTorchhttps://github.com/p-christ/Deep-Reinforcement-Learning-Algorithms-with-PyTorch
https://github.com/androidcodehub/Great-Deep-Learning-Tutorials#conferences-news
Latest Computer Vision Trends from CVPR 2019https://towardsdatascience.com/latest-computer-vision-trends-from-cvpr-2019-c07806dd570b
Interesting 2019 CVPR papershttps://medium.com/@mattmiesnieks/interesting-2019-cvpr-papers-865e303db5ca
https://github.com/androidcodehub/Great-Deep-Learning-Tutorials#deep-learning-frameworks-and-infrustructures
set-up a Paperspace GPU Serverhttps://towardsdatascience.com/how-to-set-up-a-powerful-and-cost-efficient-gpu-server-for-deep-learning-aa1de0d4ea56
Distributed ML with OpenMPIhttps://clusterone.com/tutorials/openmpi-introduction
Tensorflow 2.0 vs Mxnethttps://medium.com/@mouryarishik/tensorflow-2-0-vs-mxnet-41edd3b7574f
TensorFlow is dead, long live TensorFlow!https://hackernoon.com/tensorflow-is-dead-long-live-tensorflow-49d3e975cf04
https://github.com/androidcodehub/Great-Deep-Learning-Tutorials#great-libraries
Skorch - A scikit-learn compatible neural network library that wraps PyTorchhttps://github.com/skorch-dev/skorch
BoTorch - Bayesian Optimization in PyTorchhttps://botorch.org/
torchvision 0.3: segmentation, detection models, new datasets and morehttps://pytorch.org/blog/torchvision03/
TorchAudio: an audio library for PyTorchhttps://github.com/pytorch/audio
AudTorchhttps://github.com/audeering/audtorch
TorchAudio-Contribhttps://github.com/keunwoochoi/torchaudio-contrib
fastText - Facebook AI Research (FAIR)https://fasttext.cc/
Fairseq - Facebook AI Research (FAIR)https://github.com/pytorch/fairseq
ParlAI - dialogue models - Facebook AI Research (FAIR)https://parl.ai/
Netron - GitHubhttps://github.com/lutzroeder/netron
Netron - Web Sitehttps://www.lutzroeder.com/ai
torchvision 0.3: segmentation, detection models, new datasets and morehttps://pytorch.org/blog/torchvision03/
PyTorch Hubhttps://pytorch.org/hub
Neural Structured Learning (NSL) in TensorFlowhttps://github.com/tensorflow/neural-structured-learning
https://github.com/androidcodehub/Great-Deep-Learning-Tutorials#great-models
ResNext WSLhttps://pytorch.org/hub/facebookresearch_WSL-Images_resnext/
Deep High-Resolution Representation Learning (HRNet)https://jingdongwang2017.github.io/Projects/HRNet/
https://github.com/androidcodehub/Great-Deep-Learning-Tutorials#deep-model-conversion
Convert Full ImageNet Pre-trained Model from MXNet to PyTorchhttps://blog.paperspace.com/convert-full-imagenet-pre-trained-model-from-mxnet-to-pytorch/
Readme https://github.com/androidcodehub/Great-Deep-Learning-Tutorials#readme-ov-file
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