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-# Deep-Learning
-Assignments and presentation developed in the scope of the Deep Learning discipline, taught by Professor Dário Oliveira (FGV EMAp). Co-authored by @anacarolerthal
+# 🧠 Deep Learning
+Assignments and presentation developed in the scope of the Deep Learning discipline, taught by Professor Dário Oliveira (FGV EMAp). Co-authored by @anacarolerthal.
+
+[**Assignment 1:**](assignment01) Transfer Learning (10/10)
+
+[**Assignment 2:**](assignment02) Semantic Segmentation (10/10)
+
+[**Assignment 3:**](assignment03) Action Recognition (10/10)
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+[**Assignment 4:**](assignment04) Generative Adversarial Networks + Autoencoders (10/10)
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+[**Assignment 5:**](assignment05) Deep $k$-Means (10/10)
+
+[**Presentation:**](presentation) YUN, S. et al. Graph Transformer Networks. In: *NeurIPS*, 2019. [[pdf]](https://arxiv.org/pdf/1911.06455.pdf) [[slides]](presentation/slides.pdf)
+
+All notebooks were ran on Google Colab.
+
+The repository also contains the [`cheatsheets`](cheatsheets) folder with some useful concepts of Deep Learning I have written down during the course.
diff --git a/assignment01/code01.ipynb b/assignment01/code01.ipynb
diff --git a/assignment01/report01.pdf b/assignment01/report01.pdf
diff --git a/assignment02/code02.ipynb b/assignment02/code02.ipynb
diff --git a/assignment02/report02.pdf b/assignment02/report02.pdf
diff --git a/assignment03/code03.ipynb b/assignment03/code03.ipynb
diff --git a/assignment03/report03.pdf b/assignment03/report03.pdf