Historique de SONY - Neural Network Console

Mis à jour 3 avr. 2018 21:29:41

Date de création 25 mar. 2018 22:14:35

• 
  PALYGAP le 3 avr. 2018 21:29:41Signaler

  - RNN

• 
  PALYGAP le 3 avr. 2018 21:26:56Signaler

  Live performance monitoring

  no

  Results browser

  no

  View Valid/test set inference

  yes

  Confusion matrix

  yes

  Visualize intermediate layer activation

  no

  User test int

  no

  - Cloud

  yes

  - Cloud Trial period

  yes

  AutoML

  no

  Python shell

  no

• 
  PALYGAP le 3 avr. 2018 21:22:04Signaler

  Custom cost function

  no

  Load Caffe Models + Weights

  no

  Model checker

  yes

• 
  PALYGAP le 3 avr. 2018 21:20:52Signaler

  - LSTM

  yes

  - MLP / Auto-encoders

  yes

  Code generation

  no

  - Theano

  no

  - Tensorflow/Keras

  no

  - Caffe (v1)

  no

• 
  PALYGAP le 30 mar. 2018 05:31:33Signaler

  Tune learning parameter

  yes

  DL model training

  yes

  Inference available

  yes

  Graphical editor provided

  yes

• 
  PALYGAP le 26 mar. 2018 21:05:35Signaler

  Nom

  SONY - Neural Network Console

• 
  PALYGAP le 25 mar. 2018 22:37:30Signaler

  Web Site

  https://dl.sony.com/console/#/dashboard

• 
  PALYGAP le 25 mar. 2018 22:14:36Signaler

  Mode

  70

  Nom

  Neural Network Console

  Visibilité

  public

  Editeur

  palygap-1q7klct2

  Version of the software

  Current

  Underlaying Framework

  SONY Neural Netwok Libraries

  GPUs

  ???

  DL MODEL EDITOR

  Yes

  - CNN

  yes

  - LSTM

  Yes

  - MLP / Auto-encoders

  Yes

  - RNN

  ???

  Pretained Networks

  no

  Use Keras API

  ???

  Save Keras HDFS file (.h5)

  ???

  Save Keras model .yaml file

  ???

  Save Keras model file

  ???

  Load Keras model .yaml file

  ???

  Load Keras HDFS file (.h5)

  ???

  Code generation

  No

  - Theano

  No

  - Tensorflow/Keras

  No

  - Caffe (v1)

  No

  Custom cost function

  No

  Load Keras Models + Weights

  ???

  Load Caffe Models + Weights

  No

  Model checker

  Yes

  Datasets Management

  yes

  Experiments Mangement

  ???

  - Exp comparison

  ???

  - Prev. Exp loader

  ???

  TRAINING

  yes

  Tune learning parameter

  Yes

  Live performance monitoring

  No

  Results browser

  No

  INFERENCE

  yes

  View Valid/test set inference

  Yes

  Confusion matrix

  Yes

  Visualize intermediate layer activation

  No

  User test int

  No

  DEPLOIEMENT

  no

  - Cloud

  Yes

  but no computing environnement"

  Cloud version a paying apart from IBM

  - Cloud Trial period

  Yes

  - Desktop

  Windows

  AutoML

  No

  Browser

  ???

  Environment management

  no

  Python shell

  No

  Jupyter notebook

  no

  Tutorials

  yes

  Development Activity

  Unknown NNL - github is here : https://github.com/sony/nnabla"