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History of DEEP COGNITION - Deep Learning Studio

Last update 2018-04-04 10:22:42

Creation date 2018-03-25 22:14:35

PALYGAP on 2018-04-04 10:22:42
Development Activity
Important (2 enhanced versions have been release recently)
PALYGAP on 2018-04-03 21:26:56
Live performance monitoring
yes
Results browser
yes
View Valid/test set inference
yes
Confusion matrix
no
Visualize intermediate layer activation
yes
User test int
yes
- Cloud
yes
but no computing environnement"
yes
- Cloud Trial period
yes
AutoML
yes
Browser
yes
Python shell
yes
- Desktop
yes (any platform with python)
PALYGAP on 2018-04-03 21:22:04
Custom cost function
yes
Load Keras Models + Weights
yes
Load Caffe Models + Weights
no
Model checker
yes
Experiments Mangement
yes
- Exp comparison
yes
PALYGAP on 2018-04-03 21:20:52
- LSTM
yes
- MLP / Auto-encoders
yes
- RNN
yes
Use Keras API
yes
Save Keras HDFS file (.h5)
yes
Save Keras model .yaml file
no
Save Keras model file
no
Load Keras model .yaml file
yes
Load Keras HDFS file (.h5)
yes
Code generation
no
- Theano
no
- Tensorflow/Keras
no
- Caffe (v1)
no
PALYGAP on 2018-03-30 05:31:33
Tune learning parameter
yes
DL model training
yes
Inference available
yes
Graphical editor provided
yes
PALYGAP on 2018-03-26 21:05:35
Nombre
DEEP COGNITION - Deep Learning Studio
PALYGAP on 2018-03-25 22:39:43
Web Site
http://www.deepcognition.ai
PALYGAP on 2018-03-25 22:37:30
Web Site
http://www.deepcognition.com
PALYGAP on 2018-03-25 22:14:36
Mode
70
Nombre
Deep Learning Studio
Viewer
public
Editor
palygap-1q7klct2
Version of the software
2.0
Underlaying Framework
Apache MXNet
Development Activity
"Important
(2 enhanced versions have been release recently)"
unknown
GPUs
CUDA compatible
DL MODEL EDITOR
Yes
Changing the model is possible by editing the network graph"
DLS Better
- CNN
yes
- LSTM
Yes
- MLP / Auto-encoders
Yes
- RNN
Yes
Pretained Networks
yes (Resnet50, InceptionV3, SqueezeNet, VGG16, VGG19, WideResNet)
Use Keras API
Yes
Save Keras HDFS file (.h5)
Yes
Save Keras model .yaml file
No
Save Keras model file
No
Load Keras model .yaml file
Yes
Load Keras HDFS file (.h5)
Yes
Code generation
No
- Theano
No
- Tensorflow/Keras
No
- Caffe (v1)
No
Custom cost function
Yes
Load Keras Models + Weights
Yes
Load Caffe Models + Weights
No
Model checker
Yes
Datasets Management
yes
Experiments Mangement
Yes
- Exp comparison
Yes
- Prev. Exp loader
Yes
TRAINING
yes
Tune learning parameter
Yes
Live performance monitoring
Yes
Results browser
Yes
INFERENCE
yes
View Valid/test set inference
Yes
Confusion matrix
No
Visualize intermediate layer activation
Yes
User test int
Yes
DEPLOIEMENT
yes
- Rest API
yes
- Cloud
Yes
but no computing environnement"
Yes
- Cloud Trial period
Yes
- Desktop
Yes (any platform with python)
AutoML
Yes
Browser
Yes
Environment management
yes
Python shell
Yes
Jupyter notebook
yes
Documentation
"Minimal
(Keras API)"
"Minimal
(SONY Neural Network Library)"
???
Tutorials
yes

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