CS5242_2021 - Neural Networks and Deep Learning, NUS CS5242, 2021

Xavier Bresson

Last update: Oct 25, 2022

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Deep Learning CS5242_2021

Overview

CS5242_2021

Neural Networks and Deep Learning, NUS CS5242, 2021

Cloud Machine #1 : Google Colab (Free GPU)

Follow this Notebook installation :
https://colab.research.google.com/github/xbresson/CS5242_2021/blob/master/codes/installation/installation.ipynb
Open your Google Drive :
https://www.google.com/drive
Open in Google Drive Folder 'CS5242_2021' and go to Folder 'CS5242_2021/codes/'
Select the notebook 'file.ipynb' and open it with Google Colab using Control Click + Open With Colaboratory

Cloud Machine #2 : Binder (No GPU)

Simply click here

Local Installation for OSX & Linux

Open a Terminal and type

   # Conda installation
   curl https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -o miniconda.sh -J -L -k # Linux
   curl https://repo.continuum.io/miniconda/Miniconda3-latest-MacOSX-x86_64.sh -o miniconda.sh -J -L -k # OSX
   chmod +x miniconda.sh
   ./miniconda.sh
   source ~/.bashrc

   # Clone GitHub repo
   git clone https://github.com/xbresson/CS5242_2021.git
   cd CS5242_2021

   # Install python libraries
   conda env create -f environment.yml
   source activate deeplearn_course

   # Run the notebooks
   jupyter notebook

Local Installation for Windows

   # Install Anaconda 
   https://repo.anaconda.com/miniconda/Miniconda3-latest-Windows-x86_64.exe

   # Open an Anaconda Terminal 
   Go to Application => Anaconda3 => Anaconda Prompt 

   # Install git : Type in terminal
   conda install git 

   # Clone GitHub repo
   git clone https://github.com/xbresson/CS5242_2021.git
   cd CS5242_2021

   # Install python libraries
   conda env create -f environment_windows.yml
   conda activate deeplearn_course

   # Run the notebooks
   jupyter notebook

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Overview

CS5242_2021

Cloud Machine #1 : Google Colab (Free GPU)

Cloud Machine #2 : Binder (No GPU)

Local Installation for OSX & Linux

Local Installation for Windows

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