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--- public:res-ens:dmsml18:dmsml18 [2018/11/19 09:33] – acarlier
+++ public:res-ens:dmsml18:dmsml18 [2023/07/20 10:00] (current) – external edit 127.0.0.1
@@ Line 11: / Line 11: @@
 == Lecture time: ==
-Monday Nov 19, 2018, 5:30pm-9:30pm Hanoi Time
+Monday Nov 11, 2019, 5:30pm-9:30pm Hanoi Time
 General introduction to the course and the topic.
@@ Line 18: / Line 18: @@
 == Slides ==
-{{:public:res-ens:dmsml18:preamble.pdf|Preamble}}
+{{ :public:res-ens:dmsml18:intro.pdf |}}
 == Lab - Tutorial ==
@@ Line 25: / Line 24: @@
 The first labs consist in tutorials to get familiar with PyTorch.
-First, it is necessary to install the following packages (using anaconda)
+First, it is necessary to connect to [[https://colab.research.google.com|Google Colab]]. **This step requires a Google account**.
-pip install jupyter
-conda install numpy
+Then go to [[https://drive.google.com/open?id=1ADe_p_nZ81HCNcIMy5nk9Izp23izXVVs
-conda install pytorch torchvision -c pytorch
+|the lab repository]]. You can access 6 tutorials, to be completed sequentially.
-pip install matplotlib
+Save the tutorials into your own Google Drive, and then open them using Google Colab. Each tutorial is a Jupyter notebook, with instructions and example code, as well as exercises. The code will run remotely on a virtual machine.
+===== Lecture #2 =====
+== Lecture time: ==
+Tuesday Nov 12, 2019, 5:30pm-9:30pm Hanoi Time
+Multi-layer perceptrons
+== Lab - Tutorial ==
+Tutorials 2 and 3
+===== Lecture #3 =====
+== Lecture time: ==
+Wednesday Nov 13, 2019, 5:30pm-9:30pm Hanoi Time
+Training Neural Networks
+== Lab - Tutorial ==
+Tutorials 4 and 5
+===== Lecture #4 =====
+== Lecture time: ==
+Thursday Nov 14, 2019, 5:30pm-9:30pm Hanoi Time
+Training Neural Networks in practice
+===== Lecture #5 =====
+== Lecture time: ==
+Friday Nov 15, 2019, 5:30pm-9:30pm Hanoi Time
+Convolutional Neural Networks
+{{ :public:res-ens:dmsml18:3_cnn.pdf | Lecture slides in french }}
+Tutorial 6
+===== Lecture #6 =====
+== Lecture time: ==
+Saturday Nov 16, 2019, 5:30pm-9:30pm Hanoi Time
+A glimpse on the challenges of deep learning. {{ :public:res-ens:dmsml18:class6.pdf | Slides}}
-Then download the notebooks, run jupyter, and follow the tutorials.
+{{ :public:res-ens:dmsml18:sujet_2018.pdf |Last year's exam}}
-[[http://carlier.perso.enseeiht.fr/01_tensor_tutorial.ipynb|Tutorial 1]]