Data Science and Artificial Intelligence

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<h5><u>Using personal computer </u></h5>
 
<h5><u>Using personal computer </u></h5>
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# Download and install Anaconda
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A. Download and install Anaconda
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<div class="toccolours mw-collapsible" style="width:70%; margin-left:200px; overflow:auto;" >
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<div class="toccolours mw-collapsible" style="width:70%; margin-left:70px; overflow:auto;" >
 
<div class="mw-collapsible-content">
 
<div class="mw-collapsible-content">
 
Follow the underlisted steps to install Anaconda distribution in Linux (Ubuntu):
 
Follow the underlisted steps to install Anaconda distribution in Linux (Ubuntu):
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# source ~/.bashrc
 
# source ~/.bashrc
 
# conda list
 
# conda list
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<br> Follow the underlisted steps to install Anaconda distribution in Windows:
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# coming soon ...
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</div></div>
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B. Create virtual environment
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<div class="toccolours mw-collapsible" style="width:70%; margin-left:70px; overflow:auto;" >
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<div class="mw-collapsible-content">
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We will use the name `dsai` for thi purpose (if you choose a different name, remember to be consistent.:
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# conda create --name dsai
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# source activate dsai
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</div></div>
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C. Install packages
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<div class="toccolours mw-collapsible" style="width:70%; margin-left:70px; overflow:auto;" >
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<div class="mw-collapsible-content">
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Install PyTorch and Tensorflow packages. Depending on your system, you can install either the cpu or gpu version: <i> Do not install both.</i>
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# conda install pytorch torchvision cpuonly -c pytorch # for cpu
 +
# conda install -c aaronzs tensorflow-gpu=1.10
 +
Or;
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# conda install pytorch torchvision cudatoolkit=9.2 -c pytorch # for gpu with cuda 9.2
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# conda install -c aaronzs tensorflow-gpu=1.10
 +
 +
# conda install numpy matplotlib
 +
# conda install -c anaconda scipy==1.1.0
 +
# conda install -c conda-forge opencv tqdm
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# install jupyter notebook or jupyter lab
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conda install -c anaconda jupyter     
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conda install -c conda-forge jupyterlab
 +
pip install torchsummary
 
</div></div>
 
</div></div>
 +
<div class="toccolours mw-collapsible" style="width:70%; margin-left:70px; overflow:auto;" >
 +
<div class="mw-collapsible-content">
 +
Install PyTorch and Tensorflow packages. Depending on your system, you can install either the cpu or gpu version: <i> Do not install both.</i>
 +
# conda install pytorch torchvision cpuonly -c pytorch # for cpu
 +
# conda install -c aaronzs tensorflow-gpu=1.10
 +
Or;
 +
# conda install pytorch torchvision cudatoolkit=9.2 -c pytorch # for gpu with cuda 9.2
 +
# conda install -c aaronzs tensorflow-gpu=1.10
  
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# Create virtual environment
+
# conda install numpy matplotlib
−
# Install packages
+
# conda install -c anaconda scipy==1.1.0
 +
# conda install -c conda-forge opencv tqdm
 +
# install jupyter notebook or jupyter lab
 +
conda install -c anaconda jupyter     
 +
conda install -c conda-forge jupyterlab
 +
pip install torchsummary
  
  
 +
</div></div>
  
  

Version du 6 septembre 2019 à 11:50

Instructions

Participants needs to complete the 3 following instructions before the tutorial kick off date:

  • Installations
  • Download resources
  • Configurations


Installations

There are 2 options:

  1. Using personal computer
  2. Using Google Colab (alternative)



Using personal computer

A. Download and install Anaconda

Follow the underlisted steps to install Anaconda distribution in Linux (Ubuntu):

  1. cd /tmp
  2. curl -O https://repo.anaconda.com/archive/Anaconda3-2019.03-Linux-x86_64.sh
  3. sha256sum Anaconda3-2019.03-Linux-x86_64.sh
  4. bash Anaconda3-2019.03-Linux-x86_64.sh
  5. source ~/.bashrc
  6. conda list


Follow the underlisted steps to install Anaconda distribution in Windows:

  1. coming soon ...

B. Create virtual environment

We will use the name `dsai` for thi purpose (if you choose a different name, remember to be consistent.:

  1. conda create --name dsai
  2. source activate dsai

C. Install packages

Install PyTorch and Tensorflow packages. Depending on your system, you can install either the cpu or gpu version: Do not install both.

  1. conda install pytorch torchvision cpuonly -c pytorch # for cpu
  2. conda install -c aaronzs tensorflow-gpu=1.10

Or;

  1. conda install pytorch torchvision cudatoolkit=9.2 -c pytorch # for gpu with cuda 9.2
  2. conda install -c aaronzs tensorflow-gpu=1.10
  1. conda install numpy matplotlib
  2. conda install -c anaconda scipy==1.1.0
  3. conda install -c conda-forge opencv tqdm
  4. install jupyter notebook or jupyter lab

conda install -c anaconda jupyter conda install -c conda-forge jupyterlab pip install torchsummary

Install PyTorch and Tensorflow packages. Depending on your system, you can install either the cpu or gpu version: Do not install both.

  1. conda install pytorch torchvision cpuonly -c pytorch # for cpu
  2. conda install -c aaronzs tensorflow-gpu=1.10

Or;

  1. conda install pytorch torchvision cudatoolkit=9.2 -c pytorch # for gpu with cuda 9.2
  2. conda install -c aaronzs tensorflow-gpu=1.10
  1. conda install numpy matplotlib
  2. conda install -c anaconda scipy==1.1.0
  3. conda install -c conda-forge opencv tqdm
  4. install jupyter notebook or jupyter lab

conda install -c anaconda jupyter conda install -c conda-forge jupyterlab pip install torchsummary




Downloads

Configurations


  • Installation guide

Open a terminal and type and execute the following commands:

Anaconda

Follow the following steps to install Anaconda distribution in Ubuntu:

  1. cd /tmp
  2. curl -O https://repo.anaconda.com/archive/Anaconda3-2019.03-Linux-x86_64.sh
  3. sha256sum Anaconda3-2019.03-Linux-x86_64.sh
  4. bash Anaconda3-2019.03-Linux-x86_64.sh
  5. source ~/.bashrc
  6. conda list
Python 3 virtual environment

Follow the following steps to install:

  1. conda create --name dsai python=3
  2. conda activate dsai
TensorFlow

Follow the following steps to install:

  1. conda install -c aaronzs tensorflow-gpu=1.10
  2. conda update conda
Jupyter Notebook

Follow the following steps to install:

  1. conda install -c anaconda jupyter
Other Libraries

Follow the following steps to install:

  1. conda install -c anaconda opencv3
  2. conda install -c anaconda matplotlib
  3. conda install -c anaconda pillow
  4. conda install -c anaconda scikit-learn
  5. conda install -c anaconda scikit-image




  • Tutorial dataset
Object Recognition

Follow the following steps to install

Pose Estimation

Follow the following steps to install




  • Git repository




  • Reference materials
Lecture Notes and Slides

Follow the following steps to install

Reference papers and web resources

Follow the following steps to install




  • Survey




  • Exercises



Récupérée de « https://dsai.icube.unistra.fr/index.php?title=Deep_Learning_Tutorial_2019_installations&oldid=168 »