Самые важные статьи по глубокому обучению

Это не исчерпывающий список ни в каком смысле. Я просто подумал, что эти статьи оказали невероятное влияние на то, чтобы глубокое обучение стало таким, какое оно есть сегодня. Я также время от времени буду добавлять пару важных статей общего характера по машинному обучению в этот список. Так же я добавил несколько списков полезных материалов по машинному обучению.

• AlexNet
• GoogLeNet
• VGGNet
• ZFNet
• ResNet
• R-CNN
• Fast R-CNN
• Adversarial Images
• Generative Adversarial Networks
• Spatial Transformer Networks
• DCGAN
• Synthetic Gradients
• Memory Networks
• Mixture of Experts
• Neural Turing Machines
• Alpha Go
• Atari DQN
• Word2Vec
• GloVe
• A3C
• Gradient Descent by Gradient Descent
• Rethinking Generalization
• Densely Connected CNNs
• EBGAN
• Wasserstein GAN
• Style Transfer
• Pixel RNN
• Dynamic Coattention Networks
• Convolutional Seq2Seq Learning
• Seq2Seq
• Dropout
• Batch Norm
• Large Batch Training
• Transfer Learning
• Adam
• Speech Recognition
• Relational Networks
• Influence Functions
• ReLu
• Xavier Initialization
• Saddle Points and Non-convexity of Neural Networks
• Overcoming Catastrophic Forgetting in NNs
• Quasi-Recurrent Neural Networks
• Escaping Saddle Points Efficiently
• Progressive Growing of GANs
• Attention is All You Need
• Dynamic Routing Between Capsules
• Unsupervised Machine Translation with Monolingual Corpora
• Population Based Training of NN's
• Learned Index Structures
• Visualizing Loss Landscapes
• DenseNet
• SqueezeNet
• WaveNet
• Hidden Technical Debt in ML Systems
• MobileNets
• Learning from Imbalanced Data

Классные варианты использования машинного обучения

• Dropbox OCR
• Blend Application Submission RNNs
• Uber Customer Care NLP

ML тех подкасты

• Democratizing Machine Learning - Neil Lawrence
• Deep Learning for NLP - Richard Socher
• 2015 ICML Deep Learning Panel Discussion
• Practical Application of AI in Enterprise
• Using AI to Personlize Healthcare
• Autonomous Driving CVPR 2016 Keynote - Amnon Shashua
• From Text to Knowledge via ML - Xavier Amatriain
• Deep Visual-Semantic Alignments for Generating Image Descriptions
• Deep Learning Theoretical Motivations - Yoshua Bengio
• Learning to Learn and Compositionality with RNNs - Nando de Freitas
• Deep Advances in Generative Modeling - Alec Radford
• Adversarial Networks - Soumith Chintala
• The Next Frontier in AI: Unsupervised Learning - Yann LeCun
• ML Foundations and Methods for Precision Medicine and Healthcare - Suchi Saria
• Reprogramming the Human Genome: Why AI is Needed - Brendan Frey
• Virtual Assistant: Smart Reply - Anjuli Kannan
• Bridging the Gap Between Artificial Intelligence and Neuroscience - Alex Lavin
• Bringing Deep Learning to The Front Lines of Healthcare - Will Jack
• Deep Robotic Learning - Sergey Levine
• How AI Startups Must Compete with Google - Fei-Fei Li
• Past, Present and Future of AI Panel
• Differentiable Neural Computer - Alex Graves
• Technology, Policy and Vehicle Safety in the Age of AI - Chris Gerdes
• Attention and Memory in Deep Learning Networks - Stephen Merity
• Deep Learning in the Brain - Blake Richards
• Building Machines that See, Learn, and Think Like People - Josh Tenenbaum
• Self-Driving Cars - Sacha Arnoud
• Deep Learning and Innate Priors - Yann LeCun and Christopher Manning
• nuTonomy's Vision for Autonomous Driving - Emilio Frazzoli
• Meta-Learning and Self-Play - Ilya Sutskever
• From Generative Models to Generative Agents - Koray Kavukcuoglu
• A Neural Network Model That Can Reason - Christopher Manning
• ICLR 2018 Fireside Chat - Daphne Koller
• Test of Time NIPS 2017 - Ali Rahimi

Лучшие блоги по машинному обучению

• Andrej Karpathy
• Google Research
• Neil Lawrence
• Qure.ai
• Brandon Amos
• Denny Britz
• Moritz Hardt
• Deepmind
• Machine Learning Mastery
• Smerity
• The Neural Perspective
• Pete Warden
• Kevin Zakka
• Thomas Dinsmore
• Rohan Varma
• Anish Athalye
• Arthur Juliani
• CleverHans
• Off the Convex Path
• Sebastian Ruder
• Berkeley AI Research
• Facebook AI Research
• Salesforce Research
• Apple Machine Learning Journal
• OpenAI
• Lab41
• Depth First Learning
• The Gradient
• Distill

Лучшие телеграм каналы по машинному обучению и нейронным сетям

• https://t.me/ai_machinelearning_big_data
• https://t.me/datascienceiot
• https://t.me/ArtificialIntelligencedl
• https://t.me/Machinelearningtest
• https://t.me/machinee_learning
• https://t.me/machinelearning_ru
• https://t.me/neural
• https://t.me/programming_books_it
• https://t.me/itchannels_telegram

Другие интересные ссылки

• Neural Network Playground
• ConvNetJS Demo
• Stanford Sentiment Analysis Demo
• Deep Learning's Relation to Physics
• Training an NSFW Model - Case Study
• Interpretability of AI
• Picking up Deep Learning as an Engineer
• Feature Visualization
• Expressivity, Trainability, and Generalization in Machine Learning
• Optimization over Explanation
• Learning to Trade with RL
• AI and Digital Forgery
• Judea Pearl Interview
• State of AI in 2018
• A New Angle on L2 Regularization
• Best Practices for ML Engineering
• Bringing Performance ML to Edge Devices

#machinelearning #artificialintelligence #ai #datascience #python #programming #technology #deeplearning #coding #bigdata