François Chollet
This is how you implement a network in Chainer. Chainer, the original eager-first #deeplearning framework, has had this API since launch, in mid-2015. When PyTorch got started, it followed the Chainer template (in fact, the prototype of PyTorch was literally a fork of Chainer).
Nearly every day, I am getting ignorant messages saying, "PyTorch is an original innovation that TensorFlow/Keras copied". This is incorrect. Subclassing is a fairly obvious way to do things in Python, and Chainer had this API first. Many others followed.
I had been looking at adding a Model subclassing API to Keras as soon as late 2015 (before the Functional API even existed, and over a year before being aware of PyTorch), inspired by Chainer. Our first discussions about adding an eager execution mode also predate PyTorch.
By the time #PyTorch came out, I had been looking at its API (which is exactly the Chainer API) for 1.5 year (since the release of Chainer). It wasn't exactly a shock. There was nothing we didn't already know.
To be clear, it's a good thing that API patterns and technical innovations are cross-pollinating among deep learning framework. The #Keras API itself has a had a pretty big influence over libraries that came after. It's completely fine, and it all benefits end users.
✴️ @AI_Python_EN
This is how you implement a network in Chainer. Chainer, the original eager-first #deeplearning framework, has had this API since launch, in mid-2015. When PyTorch got started, it followed the Chainer template (in fact, the prototype of PyTorch was literally a fork of Chainer).
Nearly every day, I am getting ignorant messages saying, "PyTorch is an original innovation that TensorFlow/Keras copied". This is incorrect. Subclassing is a fairly obvious way to do things in Python, and Chainer had this API first. Many others followed.
I had been looking at adding a Model subclassing API to Keras as soon as late 2015 (before the Functional API even existed, and over a year before being aware of PyTorch), inspired by Chainer. Our first discussions about adding an eager execution mode also predate PyTorch.
By the time #PyTorch came out, I had been looking at its API (which is exactly the Chainer API) for 1.5 year (since the release of Chainer). It wasn't exactly a shock. There was nothing we didn't already know.
To be clear, it's a good thing that API patterns and technical innovations are cross-pollinating among deep learning framework. The #Keras API itself has a had a pretty big influence over libraries that came after. It's completely fine, and it all benefits end users.
✴️ @AI_Python_EN
Keras notebooks
Material used for Deep Learning related workshops for Machine Learning Tokyo (MLT)
ConvNets: colab notebook with functions for constructing #keras models. Models:
AlexNet
VGG
Inception
MobileNet
ShuffleNet
ResNet
DenseNet
Xception
Unet
SqueezeNet
YOLO
RefineNet
https://github.com/Machine-Learning-Tokyo/DL-workshop-series
✴️ @AI_Python_EN
Material used for Deep Learning related workshops for Machine Learning Tokyo (MLT)
ConvNets: colab notebook with functions for constructing #keras models. Models:
AlexNet
VGG
Inception
MobileNet
ShuffleNet
ResNet
DenseNet
Xception
Unet
SqueezeNet
YOLO
RefineNet
https://github.com/Machine-Learning-Tokyo/DL-workshop-series
✴️ @AI_Python_EN
than standard Adam? - I ran 24 experiments to find out. - The answer? Meh, not really. Full tutorial w/ #Python code here:
http://pyimg.co/asash
#DeepLearning #Keras #MachineLearning #ArtificialIntelligence #AI #DataScience
❇️ @AI_Python_en
http://pyimg.co/asash
#DeepLearning #Keras #MachineLearning #ArtificialIntelligence #AI #DataScience
❇️ @AI_Python_en
.
just published my (free) 81-page guide on learning #ComputerVision, #DeepLearning, and #OpenCV!
Includes step-by-step instructions on:
- Getting Started
- Face Applications
- Object Detection
- OCR
- Embedded/IOT
- and more!
Check it out here:
http://pyimg.co/getstarted
And if you liked it, please do give it a share to spread the word. Thank you!
#Python #Keras #MachineLearning #ArtificialIntelligence #AI
❇️ @AI_Python_EN
just published my (free) 81-page guide on learning #ComputerVision, #DeepLearning, and #OpenCV!
Includes step-by-step instructions on:
- Getting Started
- Face Applications
- Object Detection
- OCR
- Embedded/IOT
- and more!
Check it out here:
http://pyimg.co/getstarted
And if you liked it, please do give it a share to spread the word. Thank you!
#Python #Keras #MachineLearning #ArtificialIntelligence #AI
❇️ @AI_Python_EN
New tutorial! Traffic Sign Classification with #Keras and #TensorFlow 2.0
- 95% accurate
- Includes pre-trained model
- Full tutorial w/ #Python code
http://pyimg.co/5wzc5
#DeepLearning #MachineLearning #ArtificialIntelligence #DataScience #AI #computervision
❇️ @AI_Python_EN
- 95% accurate
- Includes pre-trained model
- Full tutorial w/ #Python code
http://pyimg.co/5wzc5
#DeepLearning #MachineLearning #ArtificialIntelligence #DataScience #AI #computervision
❇️ @AI_Python_EN