Stanford CS224N: NLP with Deep Learning | Winter 2019
https://www.youtube.com/watch?v=8rXD5-xhemo&list=PLoROMvodv4rOhcuXMZkNm7j3fVwBBY42z&index=1
https://www.youtube.com/watch?v=8rXD5-xhemo&list=PLoROMvodv4rOhcuXMZkNm7j3fVwBBY42z&index=1
YouTube
Stanford CS224N: NLP with Deep Learning | Winter 2019 | Lecture 1 – Introduction and Word Vectors
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3CORGu1
This lecture covers many topics within Natural Language Understanding, including:
-The Course (10 min)
-Human language and…
This lecture covers many topics within Natural Language Understanding, including:
-The Course (10 min)
-Human language and…
PoemPortrait: Google's New AI Project
https://www.lunaticai.com/2019/05/poemportrait-googles-new-ai-project.html
https://www.lunaticai.com/2019/05/poemportrait-googles-new-ai-project.html
COURSE
Probabilistic Graphical Models
Spring 2019 • Carnegie Mellon University
Lisa Lee
https://sailinglab.github.io/pgm-spring-2019/lectures/
Probabilistic Graphical Models
Spring 2019 • Carnegie Mellon University
Lisa Lee
https://sailinglab.github.io/pgm-spring-2019/lectures/
Gated Path Planning Networks (ICML 2018)
Lisa Lee
SLIDES
https://leelisa.com/pdf/gppn-slides-icml2018.pdf
Video
https://www.youtube.com/watch?v=Pnnpl-Dr5lk&feature=youtu.be&t=09s
Lisa Lee
SLIDES
https://leelisa.com/pdf/gppn-slides-icml2018.pdf
Video
https://www.youtube.com/watch?v=Pnnpl-Dr5lk&feature=youtu.be&t=09s
AI as a Service https://www.manning.com/books/ai-as-a-service
For those who are interested in machine translation study
https://www.youtube.com/watch?v=XXtpJxZBa2c
https://www.youtube.com/watch?v=XXtpJxZBa2c
YouTube
Stanford CS224N: NLP with Deep Learning | Winter 2019 | Lecture 8 – Translation, Seq2Seq, Attention
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3Cbvt8s
Professor Christopher Manning & PhD Candidate Abigail See, Stanford University
https://onlinehub.stanford.edu/
Professor…
Professor Christopher Manning & PhD Candidate Abigail See, Stanford University
https://onlinehub.stanford.edu/
Professor…
Russia's sudden change of heart on AI
https://www.msn.com/en-xl/europe/top-stories/russias-sudden-change-of-heart-on-ai/ar-AAAXoYs
https://www.msn.com/en-xl/europe/top-stories/russias-sudden-change-of-heart-on-ai/ar-AAAXoYs
Msn
Russia's sudden change of heart on AI
In a widely reported speech to a group of students on Sept. 1, 2017, "Knowledge Day" that marks the first day of the Russian school year, Vladimir Putin asserted that "the future belongs to artificial intelligence" and added that "whoever leads in AI will…
Approximate Bayesian Inference Using SGD Trajectory
code https://github.com/wjmaddox/swa_gaussian
video SWAG: Approximate Bayesian Inference Using SGD Trajectory
paper https://arxiv.org/pdf/1902.02476.pdf
code https://github.com/wjmaddox/swa_gaussian
video SWAG: Approximate Bayesian Inference Using SGD Trajectory
paper https://arxiv.org/pdf/1902.02476.pdf
GitHub
GitHub - wjmaddox/swa_gaussian: Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"
Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning" - wjmaddox/swa_gaussian
Interesting article to read about handling unlabeled data
https://arxiv.org/abs/1905.00546
https://arxiv.org/abs/1905.00546
arXiv.org
Billion-scale semi-supervised learning for image classification
This paper presents a study of semi-supervised learning with large convolutional networks. We propose a pipeline, based on a teacher/student paradigm, that leverages a large collection of...
Exponential Family Estimation via Adversarial Dynamics Embedding
Dai et al.: https://arxiv.org/abs/1904.12083
#ArtificialIntelligence #DeepLearning #MachineLearning
Dai et al.: https://arxiv.org/abs/1904.12083
#ArtificialIntelligence #DeepLearning #MachineLearning
OpenAI Gym : Make a two-dimensional bipedal robot walk forward as fast as
possible!!! https://gym.openai.com/evaluations/eval_pt663BoRS9mTUCCdGcsf4A
#AI #DeepLearning #ReinforcementLearning
possible!!! https://gym.openai.com/evaluations/eval_pt663BoRS9mTUCCdGcsf4A
#AI #DeepLearning #ReinforcementLearning
Openai
OpenAI Gym: ceobillionaire's algorithm on Walker2d-v1
See ceobillionaire's evaluation on Walker2d-v1
Yining Shi just made three Doodle Classifier experiments with Tensorflow.js:
1. Train a doodle classifier with tf.js
2. Train a doodle classifier with 345 classes
3. KNN doodle classifier
Code and demo: https://github.com/yining1023/doodleNet
#MachineLearning #TensorFlow #tensorflowjs #doodles
1. Train a doodle classifier with tf.js
2. Train a doodle classifier with 345 classes
3. KNN doodle classifier
Code and demo: https://github.com/yining1023/doodleNet
#MachineLearning #TensorFlow #tensorflowjs #doodles
GitHub
GitHub - yining1023/doodleNet: A doodle classifier(CNN), trained on all 345 categories from Quickdraw dataset.
A doodle classifier(CNN), trained on all 345 categories from Quickdraw dataset. - yining1023/doodleNet
Learning to Learn How to Learn: Self-Adaptive Visual Navigation Using Meta-Learning
Wortsman et al.: https://arxiv.org/abs/1812.00971
#ArtificialIntelligence #DeepLearning #MetaLearning
Wortsman et al.: https://arxiv.org/abs/1812.00971
#ArtificialIntelligence #DeepLearning #MetaLearning
This is last lecture in the series on Wasserstein GAN. In this lecture implementation of Wasserstein Generative Adversarial Network (WGAN) is performed in TensorFlow using Google Colab.
https://youtu.be/XK0TJPeZVbs
You can subscribe channel for more such videos
https://www.youtube.com/user/kumarahlad/featured?sub_confirmation=1
https://youtu.be/XK0TJPeZVbs
You can subscribe channel for more such videos
https://www.youtube.com/user/kumarahlad/featured?sub_confirmation=1
YouTube
Deep Learning 37: (4) Wasserstein Generative Adversarial Network (WGAN): Coding using Tensor Flow
In this lecture implementation of Wasserstein Generative Adversarial Network (WGAN) is performed in TensorFlow using Google Colab
#wasserstein#tensorflow#GAN
#wasserstein#tensorflow#GAN
"Wasserstein GAN"
Written by James Allingham: https://www.depthfirstlearning.com/2019/WassersteinGAN
#DeepLearning #GenerativeModels #GenerativeAdversarialNetworks
Written by James Allingham: https://www.depthfirstlearning.com/2019/WassersteinGAN
#DeepLearning #GenerativeModels #GenerativeAdversarialNetworks