From a4d1cb551f52f876dba11ac7225240784d58c883 Mon Sep 17 00:00:00 2001
From: Jean-Luc Parouty <Jean-Luc.Parouty@grenoble-inp.fr>
Date: Fri, 11 Sep 2020 10:33:39 +0200
Subject: [PATCH] Update README.md
---
README.ipynb | 22 ++++++++++++++--------
README.md | 2 +-
VAE/03-About-CelebA.ipynb | 2 +-
3 files changed, 16 insertions(+), 10 deletions(-)
diff --git a/README.ipynb b/README.ipynb
index e0c9db9..02c812c 100644
--- a/README.ipynb
+++ b/README.ipynb
@@ -77,12 +77,16 @@
" Episode 4 : Improving the results with data augmentation \n",
"[[GTS5] - CNN with GTSRB dataset - Full convolutions ](GTSRB/05-Full-convolutions.ipynb) \n",
" Episode 5 : A lot of models, a lot of datasets and a lot of results. \n",
- "[[GTS6] - CNN with GTSRB dataset - Full convolutions as a batch](GTSRB/06-Full-convolutions-batch.ipynb) \n",
+ "[[GTS6] - CNN with GTSRB dataset - Full convolutions as a batch](GTSRB/06-Notebook-as-a-batch.ipynb) \n",
" Episode 6 : Run Full convolution notebook as a batch \n",
- "[[GTS7] - Full convolutions Report](GTSRB/07-Full-convolutions-reports.ipynb) \n",
+ "[[GTS7] - CNN with GTSRB dataset - Show reports](GTSRB/07-Show-report.ipynb) \n",
" Episode 7 : Displaying the reports of the different jobs \n",
"[[TSB1] - Tensorboard with/from Jupyter ](GTSRB/99-Scripts-Tensorboard.ipynb) \n",
" 4 ways to use Tensorboard from the Jupyter environment \n",
+ "[[BASH1] - OAR batch script](GTSRB/batch_oar.sh) \n",
+ " Bash script for OAR batch submission of GTSRB notebook \n",
+ "[[BASH2] - SLURM batch script](GTSRB/batch_slurm.sh) \n",
+ " Bash script for SLURM batch submission of GTSRB notebooks \n",
"[[IMDB1] - Text embedding with IMDB](IMDB/01-Embedding-Keras.ipynb) \n",
" A very classical example of word embedding for text classification (sentiment analysis) \n",
"[[IMDB2] - Text embedding with IMDB - Reloaded](IMDB/02-Prediction.ipynb) \n",
@@ -97,11 +101,13 @@
" Episode 3: Attempt to predict in the longer term \n",
"[[VAE1] - Variational AutoEncoder (VAE) with MNIST](VAE/01-VAE-with-MNIST.ipynb) \n",
" Episode 1 : Model construction and Training \n",
+ "[[VAE1] - Variational AutoEncoder (VAE) with MNIST](VAE/01-VAE-with-MNIST.nbconvert.ipynb) \n",
+ " Episode 1 : Model construction and Training \n",
"[[VAE2] - Variational AutoEncoder (VAE) with MNIST - Analysis](VAE/02-VAE-with-MNIST-post.ipynb) \n",
" Episode 2 : Exploring our latent space \n",
"[[VAE3] - About the CelebA dataset](VAE/03-About-CelebA.ipynb) \n",
- " Episode 3Â : About the CelebA dataset, a more fun dataset ! \n",
- "[[VAE4] - Preparation of the CelebA dataset](VAE/04-Prepare-CelebA-batch.ipynb) \n",
+ " Episode 3Â : About the CelebA dataset, a more fun dataset ;-) \n",
+ "[[VAE4] - Preparation of the CelebA dataset](VAE/04-Prepare-CelebA-datasets.ipynb) \n",
" Episode 4Â : Preparation of a clustered dataset, batchable \n",
"[[VAE5] - Checking the clustered CelebA dataset](VAE/05-Check-CelebA.ipynb) \n",
" Episode 5Â :\\tChecking the clustered dataset \n",
@@ -111,10 +117,10 @@
" Episode 7Â : Variational AutoEncoder (VAE) with CelebA (medium res.) \n",
"[[VAE8] - Variational AutoEncoder (VAE) with CelebA - Analysis](VAE/08-VAE-withCelebA-post.ipynb) \n",
" Episode 8Â : Exploring latent space of our trained models \n",
- "[[BASH1] - OAR batch script](VAE/batch-oar.sh) \n",
- " Bash script for OAR batch submission of a notebook \n",
- "[[BASH2] - SLURM batch script](VAE/batch-slurm.sh) \n",
- " Bash script for SLURM batch submission of a notebook \n",
+ "[[BASH1] - OAR batch script](VAE/batch_oar.sh) \n",
+ " Bash script for OAR batch submission of VAE notebook \n",
+ "[[BASH2] - SLURM batch script](VAE/batch_slurm.sh) \n",
+ " Bash script for SLURM batch submission of VAE notebooks \n",
"[[ACTF1] - Activation functions](Misc/Activation-Functions.ipynb) \n",
" Some activation functions, with their derivatives. \n",
"[[NP1] - A short introduction to Numpy](Misc/Numpy.ipynb) \n",
diff --git a/README.md b/README.md
index 58aa36b..c1b9562 100644
--- a/README.md
+++ b/README.md
@@ -92,7 +92,7 @@ Some other useful informations are also available in the [wiki](https://gricad-g
[[VAE2] - Variational AutoEncoder (VAE) with MNIST - Analysis](VAE/02-VAE-with-MNIST-post.ipynb)
Episode 2 : Exploring our latent space
[[VAE3] - About the CelebA dataset](VAE/03-About-CelebA.ipynb)
- Episode 3Â : About the CelebA dataset, a more fun dataset !
+ Episode 3Â : About the CelebA dataset, a more fun dataset ;-)
[[VAE4] - Preparation of the CelebA dataset](VAE/04-Prepare-CelebA-datasets.ipynb)
Episode 4Â : Preparation of a clustered dataset, batchable
[[VAE5] - Checking the clustered CelebA dataset](VAE/05-Check-CelebA.ipynb)
diff --git a/VAE/03-About-CelebA.ipynb b/VAE/03-About-CelebA.ipynb
index 61f7ee7..f052600 100644
--- a/VAE/03-About-CelebA.ipynb
+++ b/VAE/03-About-CelebA.ipynb
@@ -7,7 +7,7 @@
"<img width=\"800px\" src=\"../fidle/img/00-Fidle-header-01.svg\"></img>\n",
"\n",
"# <!-- TITLE --> [VAE3] - About the CelebA dataset\n",
- "<!-- DESC --> Episode 3Â : About the CelebA dataset, a more fun dataset !\n",
+ "<!-- DESC --> Episode 3Â : About the CelebA dataset, a more fun dataset ;-)\n",
"<!-- AUTHOR : Jean-Luc Parouty (CNRS/SIMaP) -->\n",
"\n",
"## Objectives :\n",
--
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