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training:ds:2025:introtopytorch [2025/01/09 08:29] – created Didier Barradas Bautistatraining:ds:2025:introtopytorch [2025/04/15 05:07] (current) – Didier Barradas Bautista
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-====== Introduction to Conda for (Data) Scientists ======+====== Introduction to PyTorch for (Data) Scientists ======
  
 <WRAP group> <WRAP quarter column> <WRAP center round box 110%> {{:icon:twbs:link:w-25:h-auto:calendar3.svg?nolink&}} <tab1> <fs:26px>** Date**</fs> <WRAP group> <WRAP quarter column> <WRAP center round box 110%> {{:icon:twbs:link:w-25:h-auto:calendar3.svg?nolink&}} <tab1> <fs:26px>** Date**</fs>
  
-  * Sunday, Sep 29,2024+  * 15 April, 2025
   * 9:00 am - 1:00 pm   * 9:00 am - 1:00 pm
  
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 <WRAP center round box 110%> {{:icon:twbs:link:w-25:h-auto:globe.svg?nolink&}} <tab1> <fs:26px>** Organizer**</fs> <WRAP center round box 110%> {{:icon:twbs:link:w-25:h-auto:globe.svg?nolink&}} <tab1> <fs:26px>** Organizer**</fs>
  
-{{:icon:twbs:link:w-25:h-auto:person.svg?nolink&}} Didier Barradas Bautista \\ {{:icon:twbs:link:w-25:h-auto:headset-vr.svg?nolink&}} Visualization Core Laboratory \\ {{:icon:twbs:link:w-25:h-auto:envelope-at.svg?nolink&}} didier.barradasbautista@kaust.edu.sa </WRAP> </WRAP>+{{:icon:twbs:link:w-25:h-auto:person.svg?nolink&}} Didier Barradas Bautista \\  
 +{{:icon:twbs:link:w-25:h-auto:headset-vr.svg?nolink&}} Visualization Core Laboratory \\  
 +{{:icon:twbs:link:w-25:h-auto:envelope-at.svg?nolink&}} didier.barradasbautista@kaust.edu.sa  
 + 
 +/* 
 +{{:icon:twbs:link:w-25:h-auto:person.svg?nolink&}}   Tiziana Ricciardelli \\  
 +{{:icon:twbs:link:w-25:h-auto:book.svg?nolink&}}  KCC \\  
 +{{:icon:twbs:link:w-25:h-auto:envelope-at.svg?nolink&}} tiziana.ricciardelli@kaust.edu.sa 
 +*/ 
 + 
 +</WRAP> </WRAP>
  
 <WRAP quarter column> <WRAP center round box 100%>{{:icon:twbs:link:w-25:h-auto:person-add.svg?nolink&}} <tab1> <fs:26px>** Register**</fs> <WRAP quarter column> <WRAP center round box 100%>{{:icon:twbs:link:w-25:h-auto:person-add.svg?nolink&}} <tab1> <fs:26px>** Register**</fs>
  
-<wrap em button> [[https://kaustforms.formstack.com/forms/conda_24 |Register Here]] </wrap> \\+<wrap em button> [[ https://kaustforms.formstack.com/forms/pytorch_25|Register Here]] </wrap> \\
 <wrap indent></wrap> \\ <wrap indent></wrap> \\
 <wrap indent></wrap> \\ <wrap indent></wrap> \\
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 <WRAP group> <WRAP third column> <WRAP group> <WRAP third column>
-{{training:ds:2024:anaconda.svg}}+{{training:ds:2024:pytorch_logo_icon.svg}}
 /* /*
 {{  wiki:highlights:2023:cpv-cop.png?direct&  }} {{  wiki:highlights:2023:cpv-cop.png?direct&  }}
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  <fs:26px>** Workshop Materials**</fs>  <fs:26px>** Workshop Materials**</fs>
  
-  * Slides: [[https://kaust-my.sharepoint.com/:p:/g/personal/barradd_kaust_edu_sa/EYyXPZwMbv9Pqx9V3YxH4okBBDohnlV67ZNw7BwDp4cUog?e=UCv8UU | here]]+  * Slides: [[https://kaust-my.sharepoint.com/:p:/g/personal/barradd_kaust_edu_sa/ET_hM92YzQlFmU0zyaaRMkoBPFMADZPXreo_wwC77TpYBg?e=WjgrjW | here]]
 /*  * Livestream: [[https://youtube.com/live/7iZmdWtH97E?feature=share | watch recording]] */ /*  * Livestream: [[https://youtube.com/live/7iZmdWtH97E?feature=share | watch recording]] */
   * Etherpath:[[https://pad.carpentries.org/2024-09-26-kaust-vislab]|here]]   * Etherpath:[[https://pad.carpentries.org/2024-09-26-kaust-vislab]|here]]
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  <fs:26px>** How to Prepare?**</fs>  <fs:26px>** How to Prepare?**</fs>
  
-  * Here is the material we will follow :[[https://carpentries-incubator.github.io/introduction-to-conda-for-data-scientists/| Conda]]. +  * Here is the material we will follow :[[https://pytorch.org/tutorials/beginner/basics/intro.html| PyTorch]]. 
-  * Local Setup : [[https://carpentries-incubator.github.io/introduction-to-conda-for-data-scientists/setup|Here]]. +  * As alternative, read the material here : [[https://www.learnpytorch.io/ | Learn PyTorch for Deep Learning: Zero to Mastery book]]. 
-  * Public Binder : [[https://github.com/kaust-vislab/kvl-binder-serv-public|here]]+  * Local Setup : [[https://pytorch.org/get-started/locally/|Here]]. 
 +  * Binder : [[https://github.com/kaust-vislab/introduction-to-data-science-workshop|here]]
   * **KAUSTians you will be able to use:**   * **KAUSTians you will be able to use:**
   * The [[https://classhub.kaust.edu.sa/course/binder-ws/|Classhub]], please create a [[https://github.com/|GitHub]] account in order to use it   * The [[https://classhub.kaust.edu.sa/course/binder-ws/|Classhub]], please create a [[https://github.com/|GitHub]] account in order to use it
-  * After you create the GitHub account, get access [[https://assembly.kaust.edu.sa/form/c0944092-f221-4a23-b471-0c9dd6e4d879 +  * After you create the GitHub account, get access [[https://assembly.kaust.edu.sa/form/ffe5352f-c502-4d26-8975-e50c71a58a8a |here]]
-|here]]+
   * [[https://jupyter.kaust.edu.sa/hub/login|JupyterHub]], use your portal credentials to log in   * [[https://jupyter.kaust.edu.sa/hub/login|JupyterHub]], use your portal credentials to log in
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 ===== Overview ===== ===== Overview =====
  
-Conda is an open-source package and environment management system that runs on Windows, macOS, and Linux. Conda installs, runs, and updates packages and their dependencies. Conda easily creates, saves, loads, and switches between environments on your local computer. While Conda was created for Python programs, it can package and distribute software for any language, such as R, Ruby, Lua, Scala, Java, JavaScript, C/ C++, and FORTRAN. This lesson motivates using Conda as a development tool for building and sharing project-specific software environments that facilitate reproducible (data) science workflows.+PyTorch is an open-source deep learning framework developed by Facebook's AI Research Lab (FAIR). It is widely used for building and training neural networks due to its flexibility and ease of use. Learning PyTorch is beneficial because it is one of the most popular artificial intelligence and machine learning frameworks. It is extensively used in academia and industry, powering applications from simple image classifiers to complex systems like self-driving cars and large language models.
  
 This hands-on lesson is part of the Introduction to Data Science Workshop Series offered by KVL as part of our ongoing efforts to build core data science skills capacity both at KAUST and within the Kingdom of Saudi Arabia (KSA). This hands-on lesson is part of the Introduction to Data Science Workshop Series offered by KVL as part of our ongoing efforts to build core data science skills capacity both at KAUST and within the Kingdom of Saudi Arabia (KSA).
  
-If you have any questions, please get in touch with us at [[mailto:help@vis.kaust.edu.sa|help@vis.kaust.edu.sa]].+If you have any questions, please contact us at [[mailto:help@vis.kaust.edu.sa|help@vis.kaust.edu.sa]].
  
  
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 ^Time  ^Topic| ^Time  ^Topic|
-^09:00 |Introduction to Conda   | +^09:00 |Introduction to PyTorch | 
-^09:30 |Working with Environments | +^09:30 |Autograd: Automatic Differentiation | 
-^10:00 |Using Packages and Channels                 | +^10:00 |Building Neural Networks | 
-^11:00 |Sharing Environments                              | +^11:00 |Training a Model on a Dataset | 
-^12:00 |Managing GPU dependencies                   |+^12:00 |Advanced Topics |
  
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