Artificial Intelligence Full Course | Artificial Intelligence Tutorial for Beginners
https://www.youtube.com/watch?v=JMUxmLyrhSk
https://www.youtube.com/watch?v=JMUxmLyrhSk
YouTube
Artificial Intelligence Full Course | Artificial Intelligence Tutorial for Beginners | Edureka
🔥PGP in Generative AI and ML in collaboration with Illinois Tech: https://www.edureka.co/executive-programs/pgp-generative-ai-machine-learning-certification-training
🔥Generative AI Course: Master's Program: https://www.edureka.co/masters-program/generative…
🔥Generative AI Course: Master's Program: https://www.edureka.co/masters-program/generative…
Artificial Intelligence Tutorial for Beginners | Artificial Intelligence
https://www.youtube.com/watch?v=WZVAfLreIwM
https://www.youtube.com/watch?v=WZVAfLreIwM
YouTube
Artificial Intelligence Tutorial for Beginners | Artificial Intelligence Explained | Edureka
** Machine Learning Engineer Masters Program: https://www.edureka.co/masters-program/machine-learning-engineer-training **
This Edureka video on "Artificial Intelligence Tutorial" will provide you with a detailed and comprehensive knowledge of Artificial…
This Edureka video on "Artificial Intelligence Tutorial" will provide you with a detailed and comprehensive knowledge of Artificial…
Alexa, Alex, or Al?
3 Suggestions to Fight Gender Biases in AI Assistants
https://towardsdatascience.com/alexa-alex-or-al-7a7e28fb4736
3 Suggestions to Fight Gender Biases in AI Assistants
https://towardsdatascience.com/alexa-alex-or-al-7a7e28fb4736
Towards Data Science
Alexa, Alex, or Al?
3 Suggestions to Fight Gender Biases in AI Assistants
Introducing Google Research Football: A Novel Reinforcement Learning Environment
http://ai.googleblog.com/2019/06/introducing-google-research-football.html
http://ai.googleblog.com/2019/06/introducing-google-research-football.html
research.google
Introducing Google Research Football: A Novel Reinforcement Learning Environment
Posted by Karol Kurach, Research Lead and Olivier Bachem, Research Scientist, Google Research, Zürich The goal of reinforcement learning (RL) is ...
An Explicitly Relational Neural Network Architecture
https://arxiv.org/abs/1905.10307
https://arxiv.org/abs/1905.10307
arXiv.org
An Explicitly Relational Neural Network Architecture
With a view to bridging the gap between deep learning and symbolic AI, we present a novel end-to-end neural network architecture that learns to form propositional representations with an...
Chip design drastically reduces energy needed to compute with light
http://news.mit.edu/2019/ai-chip-light-computing-faster-0605
http://news.mit.edu/2019/ai-chip-light-computing-faster-0605
MIT News
Chip design drastically reduces energy needed to compute with light
MIT researchers have developed a “photonic” artificial intelligence (AI) accelerator that computes using light instead of electricity — and consumes relatively little power in the process — to run massive neural networks millions of times more efficiently…
AI for Everyone: Myth or Reality?
https://towardsdatascience.com/ai-for-everyone-myth-or-reality-44edc24f7982?source=collection_home---4------1-----------------------
https://towardsdatascience.com/ai-for-everyone-myth-or-reality-44edc24f7982?source=collection_home---4------1-----------------------
Towards Data Science
AI for Everyone: Myth or Reality?
A Summarisation of Facebook’s research paper titled “Does Object Recognition Work for Everyone?”
Forwarded from Machinelearning
One-Shot Learning with Siamese Networks, Contrastive Loss, and Triplet Loss for Face Recognition
https://machinelearningmastery.com/one-shot-learning-with-siamese-networks-contrastive-and-triplet-loss-for-face-recognition/
https://machinelearningmastery.com/one-shot-learning-with-siamese-networks-contrastive-and-triplet-loss-for-face-recognition/
Invertible Residual Networks
Official Pytorch implementation of i-ResNets.
Article: http://proceedings.mlr.press/v97/behrmann19a.html
Github: https://github.com/jhjacobsen/invertible-resnet
Official Pytorch implementation of i-ResNets.
Article: http://proceedings.mlr.press/v97/behrmann19a.html
Github: https://github.com/jhjacobsen/invertible-resnet
PMLR
Invertible Residual Networks
We show that standard ResNet architectures can be made invertible, allowing the same model to be used for classification, density estimation, and generation....
Gossip-based Actor-Learner Architectures for Deep Reinforcement Learning
https://arxiv.org/abs/1906.04585
https://arxiv.org/abs/1906.04585
Forwarded from Machinelearning
Applying AutoML to Transformer Architectures
http://ai.googleblog.com/2019/06/applying-automl-to-transformer.html
http://ai.googleblog.com/2019/06/applying-automl-to-transformer.html
Googleblog
Applying AutoML to Transformer Architectures
A Game of Words: Vectorization, Tagging, and Sentiment Analysis
https://towardsdatascience.com/a-game-of-words-vectorization-tagging-and-sentiment-analysis-c78ff9a07e42?source=topic_page---------------------------20
https://towardsdatascience.com/a-game-of-words-vectorization-tagging-and-sentiment-analysis-c78ff9a07e42?source=topic_page---------------------------20
Towards Data Science
A Game of Words: Vectorization, Tagging, and Sentiment Analysis
Analyzing words from Game of Thrones Book 1 with Natural Language Processing (Part 2)
Monotonic Infinite Lookback Attention for Simultaneous Machine Translation
Paper.: https://arxiv.org/abs/1906.05218
Paper.: https://arxiv.org/abs/1906.05218
arXiv.org
Monotonic Infinite Lookback Attention for Simultaneous Machine Translation
Simultaneous machine translation begins to translate each source sentence
before the source speaker is finished speaking, with applications to live and
streaming scenarios. Simultaneous systems...
before the source speaker is finished speaking, with applications to live and
streaming scenarios. Simultaneous systems...
Teaching artificial intelligence to connect senses like vision and touch
http://news.mit.edu/2019/teaching-ai-to-connect-senses-vision-touch-0617
http://news.mit.edu/2019/teaching-ai-to-connect-senses-vision-touch-0617
MIT News
Teaching artificial intelligence to connect senses like vision and touch
An artificial intelligence system from MIT CSAIL uses machine learning to create realistic tactile signals from visual inputs, and predict which object and what part is being touched directly from those tactile inputs.
A fastai/Pytorch implementation of MixMatch
Understanding the new state of the art in semi-supervised learning
https://towardsdatascience.com/a-fastai-pytorch-implementation-of-mixmatch-314bb30d0f99
Understanding the new state of the art in semi-supervised learning
https://towardsdatascience.com/a-fastai-pytorch-implementation-of-mixmatch-314bb30d0f99
Medium
A fastai/Pytorch implementation of MixMatch
Understanding the new state of the art in semi-supervised learning