Week 8 (part c) CS294-158 Deep Unsupervised Learning (4/3/19) -- Ilya Sutskever
https://www.youtube.com/watch?v=X-B3nAN7YRM
https://www.youtube.com/watch?v=X-B3nAN7YRM
YouTube
Week 8 (part c) CS294-158 Deep Unsupervised Learning (4/3/19) -- Ilya Sutskever
UC Berkeley CS294-158 Deep Unsupervised Learning (Spring 2019)
Instructors: Pieter Abbeel, Xi (Peter) Chen, Jonathan Ho, Aravind Srinivas
https://sites.google.com/view/berkele...
Week 8c Lecture Contents:
- Ilya Sutskever guest lecture on GPT-2
Instructors: Pieter Abbeel, Xi (Peter) Chen, Jonathan Ho, Aravind Srinivas
https://sites.google.com/view/berkele...
Week 8c Lecture Contents:
- Ilya Sutskever guest lecture on GPT-2
Take Your Best Selfie Automatically, with Photobooth on Pixel 3
http://ai.googleblog.com/2019/04/take-your-best-selfie-automatically.html
http://ai.googleblog.com/2019/04/take-your-best-selfie-automatically.html
Googleblog
Take Your Best Selfie Automatically, with Photobooth on Pixel 3
MorphNet: Towards Faster and Smaller Neural Networks
http://ai.googleblog.com/2019/04/morphnet-towards-faster-and-smaller.html
http://ai.googleblog.com/2019/04/morphnet-towards-faster-and-smaller.html
Googleblog
MorphNet: Towards Faster and Smaller Neural Networks
How I used Python to analyze Game of Thrones
https://medium.freecodecamp.org/how-i-used-python-to-analyze-game-of-thrones-503a96028ce6
https://medium.freecodecamp.org/how-i-used-python-to-analyze-game-of-thrones-503a96028ce6
freeCodeCamp.org
How I used Python to analyze Game of Thrones
By Rocky Kev I wanted to learn Python for a long time, but I could never find a reason. When my company had a bunch of daily reports that needed to be generated, I realized I had an opportunity to explore Python to cut out all the repetition. This ar...
A Gentle Introduction to Pooling Layers for Convolutional Neural Networks
https://machinelearningmastery.com/pooling-layers-for-convolutional-neural-networks/
https://machinelearningmastery.com/pooling-layers-for-convolutional-neural-networks/
SpecAugment: A New Data Augmentation Method for Automatic Speech Recognition
http://ai.googleblog.com/2019/04/specaugment-new-data-augmentation.html
http://ai.googleblog.com/2019/04/specaugment-new-data-augmentation.html
Googleblog
SpecAugment: A New Data Augmentation Method for Automatic Speech Recognition
10 Practical Tips for the Successful Adoption of Your Machine Learning Products
https://medium.com/omdena/10-practical-tips-for-the-successful-adoption-of-your-machine-learning-products-e68dd1b486c8
https://medium.com/omdena/10-practical-tips-for-the-successful-adoption-of-your-machine-learning-products-e68dd1b486c8
Medium
10 Practical Tips for the Successful Adoption of Your Machine Learning Products
Hands-on tips for companies to build Machine Learning Products that are being adopted by their users and customers.
Architectural Innovations in Convolutional Neural Networks for Image Classification
https://machinelearningmastery.com/review-of-architectural-innovations-for-convolutional-neural-networks-for-image-classification/
https://machinelearningmastery.com/review-of-architectural-innovations-for-convolutional-neural-networks-for-image-classification/
MachineLearningMastery.com
Convolutional Neural Network Model Innovations for Image Classification - MachineLearningMastery.com
A Gentle Introduction to the Innovations in LeNet, AlexNet, VGG, Inception, and ResNet Convolutional Neural Networks.
Convolutional neural networks are comprised of two very simple elements, namely convolutional layers and pooling layers.
Although simple…
Convolutional neural networks are comprised of two very simple elements, namely convolutional layers and pooling layers.
Although simple…
Увеличение видео 1080P до 4К, или Как я научился не волноваться и полюбил апскейл с помощью нейросетей
https://habr.com/ru/post/446032/
https://habr.com/ru/post/446032/
Хабр
Увеличение видео 1080P до 4K, или Как я научился не волноваться и полюбил апскейл с помощью нейросетей
Читая недавно очередную статью про апскейл ( Upscale — масштабирование изображения до более высокого разрешения), на этот раз про коммерческий продукт Topaz AI Gigapixel, я оставил комментарий...
Evaluating the Unsupervised Learning of Disentangled Representations
http://ai.googleblog.com/2019/04/evaluating-unsupervised-learning-of.html
http://ai.googleblog.com/2019/04/evaluating-unsupervised-learning-of.html
Googleblog
Evaluating the Unsupervised Learning of Disentangled Representations
Hyperparameter optimization in python. Part 1: Scikit-Optimize.
https://towardsdatascience.com/hyperparameter-optimization-in-python-part-1-scikit-optimize-754e485d24fe
https://towardsdatascience.com/hyperparameter-optimization-in-python-part-1-scikit-optimize-754e485d24fe
MuseNet deep neural network that can generate 4-minute musical compositions with 10 different instruments
https://openai.com/blog/musenet/
https://openai.com/blog/musenet/
Openai
MuseNet
We’ve created MuseNet, a deep neural network that can generate 4-minute musical compositions with 10 different instruments, and can combine styles from country to Mozart to the Beatles. MuseNet was not explicitly programmed with our understanding of music…
How to Implement VGG, Inception and ResNet Modules for Convolutional Neural Networks from Scratch
https://machinelearningmastery.com/how-to-implement-major-architecture-innovations-for-convolutional-neural-networks/
https://machinelearningmastery.com/how-to-implement-major-architecture-innovations-for-convolutional-neural-networks/
How to Start Competing on Kaggle
https://towardsdatascience.com/how-to-begin-competing-on-kaggle-bd9b5f32dbbc
https://towardsdatascience.com/how-to-begin-competing-on-kaggle-bd9b5f32dbbc
A pytorch-toolbelt is a Python library with a set of bells and whistles for PyTorch for fast R&D prototyping and Kaggle farming
https://github.com/BloodAxe/pytorch-toolbelt
https://github.com/BloodAxe/pytorch-toolbelt
GitHub
GitHub - BloodAxe/pytorch-toolbelt: PyTorch extensions for fast R&D prototyping and Kaggle farming
PyTorch extensions for fast R&D prototyping and Kaggle farming - BloodAxe/pytorch-toolbelt
A Gentle Introduction to 1×1 Convolutions to Reduce the Complexity of Convolutional Neural Networks
https://machinelearningmastery.com/introduction-to-1x1-convolutions-to-reduce-the-complexity-of-convolutional-neural-networks/
https://machinelearningmastery.com/introduction-to-1x1-convolutions-to-reduce-the-complexity-of-convolutional-neural-networks/
MachineLearningMastery.com
A Gentle Introduction to 1×1 Convolutions to Manage Model Complexity - MachineLearningMastery.com
Pooling can be used to down sample the content of feature maps, reducing their width and height whilst maintaining their salient features. A problem with deep convolutional neural networks is that the number of feature maps often increases with the depth…
Forwarded from Artificial Intelligence
Announcing the 6th Fine-Grained Visual Categorization Workshop
http://ai.googleblog.com/2019/04/announcing-6th-fine-grained-visual.html
http://ai.googleblog.com/2019/04/announcing-6th-fine-grained-visual.html
Googleblog
Announcing the 6th Fine-Grained Visual Categorization Workshop