illustrated Artificial Intelligence cheatsheets covering the content of the CS 221 class
Link: https://stanford.edu/~shervine/teaching/cs-221/
Reflex-based models with Machine Learning: https://stanford.edu/~shervine/teaching/cs-221/cheatsheet-reflex-models
Link: https://stanford.edu/~shervine/teaching/cs-221/
Reflex-based models with Machine Learning: https://stanford.edu/~shervine/teaching/cs-221/cheatsheet-reflex-models
stanford.edu
Teaching - CS 221
Teaching page of Shervine Amidi, Graduate Student at Stanford University.
How degenerate is the parametrization of neural networks with the ReLU activation function?
https://arxiv.org/abs/1905.09803
https://arxiv.org/abs/1905.09803
How to Perform Object Detection With YOLOv3 in Keras
https://machinelearningmastery.com/how-to-perform-object-detection-with-yolov3-in-keras/
https://machinelearningmastery.com/how-to-perform-object-detection-with-yolov3-in-keras/
Forwarded from Artificial Intelligence
Unsupervised Learning with Graph Neural Networks
video: http://www.ipam.ucla.edu/programs/workshops/workshop-iv-deep-geometric-learning-of-big-data-and-applications/?tab=schedule
guide: http://helper.ipam.ucla.edu/publications/glws4/glws4_15546.pdf
video: http://www.ipam.ucla.edu/programs/workshops/workshop-iv-deep-geometric-learning-of-big-data-and-applications/?tab=schedule
guide: http://helper.ipam.ucla.edu/publications/glws4/glws4_15546.pdf
IPAM
Workshop IV: Deep Geometric Learning of Big Data and Applications - IPAM
Augmented Neural ODEs
Github: https://github.com/EmilienDupont/augmented-neural-odes
Article: https://arxiv.org/abs/1904.01681
Github: https://github.com/EmilienDupont/augmented-neural-odes
Article: https://arxiv.org/abs/1904.01681
GitHub
GitHub - EmilienDupont/augmented-neural-odes: Pytorch implementation of Augmented Neural ODEs :sunflower:
Pytorch implementation of Augmented Neural ODEs :sunflower: - EmilienDupont/augmented-neural-odes
SimpleSelfAttention
The purpose of this repository is two-fold:
-demonstrate improvements brought by the use of a self-attention layer in an image -classification model.
introduce a new layer which I call SimpleSelfAttention
https://github.com/sdoria/SimpleSelfAttention
The purpose of this repository is two-fold:
-demonstrate improvements brought by the use of a self-attention layer in an image -classification model.
introduce a new layer which I call SimpleSelfAttention
https://github.com/sdoria/SimpleSelfAttention
GitHub
GitHub - sdoria/SimpleSelfAttention: A simpler version of the self-attention layer from SAGAN, and some image classification results.
A simpler version of the self-attention layer from SAGAN, and some image classification results. - sdoria/SimpleSelfAttention
How to Train an Object Detection Model to Find Kangaroos in Photographs (R-CNN with Keras)
https://machinelearningmastery.com/how-to-train-an-object-detection-model-with-keras/
https://machinelearningmastery.com/how-to-train-an-object-detection-model-with-keras/
MachineLearningMastery.com
How to Train an Object Detection Model with Keras - MachineLearningMastery.com
Object detection is a challenging computer vision task that involves predicting both where the objects are in the image and what type of objects were detected. The Mask Region-based Convolutional Neural Network, or Mask R-CNN, model is one of the state-of…
EfficientNets
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
link: https://arxiv.org/abs/1905.11946.
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
link: https://arxiv.org/abs/1905.11946.
arXiv.org
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
Convolutional Neural Networks (ConvNets) are commonly developed at a fixed resource budget, and then scaled up for better accuracy if more resources are available. In this paper, we systematically...
Multi-Sample Dropout for Accelerated Training and Better Generalization
Link: https://arxiv.org/abs/1905.09788
Link: https://arxiv.org/abs/1905.09788
arXiv.org
Multi-Sample Dropout for Accelerated Training and Better Generalization
Dropout is a simple but efficient regularization technique for achieving better generalization of deep neural networks (DNNs); hence it is widely used in tasks based on DNNs. During training,...
A Gentle Introduction to Deep Learning for Face Recognition
https://machinelearningmastery.com/introduction-to-deep-learning-for-face-recognition/
https://machinelearningmastery.com/introduction-to-deep-learning-for-face-recognition/
MachineLearningMastery.com
A Gentle Introduction to Deep Learning for Face Recognition - MachineLearningMastery.com
Face recognition is the problem of identifying and verifying people in a photograph by their face. It is a task that is trivially performed by humans, even under varying light and when faces are changed by age or obstructed with accessories and facial hair.…
How to Perform Face Detection with Deep Learning in Keras
https://machinelearningmastery.com/how-to-perform-face-detection-with-classical-and-deep-learning-methods-in-python-with-keras/
https://machinelearningmastery.com/how-to-perform-face-detection-with-classical-and-deep-learning-methods-in-python-with-keras/
Learning Perceptually-Aligned Representations via Adversarial Robustness
Article: https://arxiv.org/abs/1906.00945
Github: https://github.com/MadryLab/robust_representations
Article: https://arxiv.org/abs/1906.00945
Github: https://github.com/MadryLab/robust_representations
Forwarded from Artificial Intelligence
YouTube
DeepMind Made a Math Test For Neural Networks
📝 The paper "Analysing Mathematical Reasoning Abilities of Neural Models" is available here:
https://arxiv.org/abs/1904.01557
❤️ Pick up cool perks on our Patreon page: https://www.patreon.com/TwoMinutePapers
🙏 We would like to thank our generous Patreon…
https://arxiv.org/abs/1904.01557
❤️ Pick up cool perks on our Patreon page: https://www.patreon.com/TwoMinutePapers
🙏 We would like to thank our generous Patreon…
Introducing TensorNetwork, an Open Source Library for Efficient Tensor Calculations
http://ai.googleblog.com/2019/06/introducing-tensornetwork-open-source.html
http://ai.googleblog.com/2019/06/introducing-tensornetwork-open-source.html
research.google
Introducing TensorNetwork, an Open Source Library for Efficient Tensor Calculati
Posted by Chase Roberts, Research Engineer, Google AI and Stefan Leichenauer, Research Scientist, X Many of the world's toughest scientific chall...
Free COURSE. CS Deep Reinforcement Learning UC Berkeley
Video Lectures: https://www.youtube.com/playlist?list=PLkFD6_40KJIxJM..
Lecture Material: http://rail.eecs.berkeley.edu/deeprlcourse/
Video Lectures: https://www.youtube.com/playlist?list=PLkFD6_40KJIxJM..
Lecture Material: http://rail.eecs.berkeley.edu/deeprlcourse/
Youtube
Oops! Something went wrong. - YouTube
Enjoy the videos and music you love, upload original content, and share it all with friends, family, and the world on YouTube.
Welcome to TensorWatch
TensorWatch is a debugging and visualization tool designed for deep learning and reinforcement learning from Microsoft Research. It works in Jupyter Notebook to show real-time visualizations of your machine learning training and perform several other key visualizations of your models and data.
https://github.com/microsoft/tensorwatch/
TensorWatch is a debugging and visualization tool designed for deep learning and reinforcement learning from Microsoft Research. It works in Jupyter Notebook to show real-time visualizations of your machine learning training and perform several other key visualizations of your models and data.
https://github.com/microsoft/tensorwatch/
GitHub
GitHub - microsoft/tensorwatch: Debugging, monitoring and visualization for Python Machine Learning and Data Science
Debugging, monitoring and visualization for Python Machine Learning and Data Science - microsoft/tensorwatch