From 753460b8ddf359c63c676bc6db52a6d85563fbd5 Mon Sep 17 00:00:00 2001
From: DejasDejas <38346343+DejasDejas@users.noreply.github.com>
Date: Thu, 28 May 2020 12:26:31 +0200
Subject: [PATCH] Update README.md

---
 README.md | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md
index c1a77a943..6888840a3 100644
--- a/README.md
+++ b/README.md
@@ -37,7 +37,7 @@ The MNIST database of handwritten digits, available from this [link](http://yann
 
 ## Open Binary MNIST notebook:
 
-[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)]()
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1VGAmCEdTvuRWWpdvQZliDiIC4t-quP36)
 
 ## Results on MNIST:
 
@@ -66,7 +66,7 @@ The Omniglot data set is designed for developing more human-like learning algori
 
 ## Open Binary Omniglot notebook:
 
-[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)]()
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1WNfu6Aas8DD4l7EkSFndIVIqCpp8spik)
 
 ## Results on Omniglot classification with data train (80% train, 10% validation and 10% test):
 ### Loss/ACC: with 10 epochs.
@@ -92,7 +92,7 @@ In this part, we present results obtained with [Matching Networks for One Shot L
 
 ## Open binary few shot Omniglot notebook:
 
-[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)]()
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1WN5kIeBl209StRZJOvf3ek6bHQslmNId)
 
 ## Results on Omniglot few shot learning:
 ### ACC: with this repository with 10 epochs.
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