How to Load Large Datasets From Directories for Deep Learning with Keras
https://machinelearningmastery.com/how-to-load-large-datasets-from-directories-for-deep-learning-with-keras/
https://machinelearningmastery.com/how-to-load-large-datasets-from-directories-for-deep-learning-with-keras/
MachineLearningMastery.com
How to Load Large Datasets From Directories for Deep Learning in Keras - MachineLearningMastery.com
There are conventions for storing and structuring your image dataset on disk in order to make it fast and efficient to load and when training and evaluating deep learning models. Once structured, you can use tools like the ImageDataGenerator class in the…
Hyperbolic Image Embeddings
https://github.com/KhrulkovV/hyperbolic-image-embeddings
https://github.com/KhrulkovV/hyperbolic-image-embeddings
GitHub
GitHub - leymir/hyperbolic-image-embeddings: Supplementary code for the paper "Hyperbolic Image Embeddings".
Supplementary code for the paper "Hyperbolic Image Embeddings". - GitHub - leymir/hyperbolic-image-embeddings: Supplementary code for the paper "Hyperbolic Image Embeddings".
Forwarded from Artificial Intelligence
Review: Residual Attention Network — Attention-Aware Features (Image Classification)
https://towardsdatascience.com/review-residual-attention-network-attention-aware-features-image-classification-7ae44c4f4b8
https://towardsdatascience.com/review-residual-attention-network-attention-aware-features-image-classification-7ae44c4f4b8
Medium
Review: Residual Attention Network — Attention-Aware Features (Image Classification)
Outperforms Pre-Activation ResNet, WRN, Inception-ResNet, ResNeXt
How to Configure Image Data Augmentation When Training Deep Learning Neural Networks
https://machinelearningmastery.com/how-to-configure-image-data-augmentation-when-training-deep-learning-neural-networks/
https://machinelearningmastery.com/how-to-configure-image-data-augmentation-when-training-deep-learning-neural-networks/
MachineLearningMastery.com
How to Configure Image Data Augmentation in Keras - MachineLearningMastery.com
Image data augmentation is a technique that can be used to artificially expand the size of a training dataset by creating modified versions of images in the dataset. Training deep learning neural network models on more data can result in more skillful models…
Gentle Dive into Math Behind Convolutional Neural Networks
https://towardsdatascience.com/gentle-dive-into-math-behind-convolutional-neural-networks-79a07dd44cf9
https://towardsdatascience.com/gentle-dive-into-math-behind-convolutional-neural-networks-79a07dd44cf9
Medium
Gentle Dive into Math Behind Convolutional Neural Networks
Mysteries of Neural Networks Part V
How to Use Test-Time Augmentation to Improve Model Performance for Image Classification
https://machinelearningmastery.com/how-to-use-test-time-augmentation-to-improve-model-performance-for-image-classification/
https://machinelearningmastery.com/how-to-use-test-time-augmentation-to-improve-model-performance-for-image-classification/
Основы Natural Language Processing для текста
https://habr.com/ru/company/Voximplant/blog/446738/
https://habr.com/ru/company/Voximplant/blog/446738/
Хабр
Основы Natural Language Processing для текста
Обработка естественного языка сейчас не используются разве что в совсем консервативных отраслях. В большинстве технологических решений распознавание и обработка «человеческих» языков давно...
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...