This workshop will introduce participants to Generative Adversarial Networks (GANs). We will demonstrate the core techniques of GANs, including how to use Deep Convolutional GANs (DCGANs) to generate images using PyTorch. A basic understanding of the topics covered in previous sessions is assumed. Having working experience with Python, Jupyter Notebooks, and linear algebra will be…
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Jupyter Notebook
Learning Convolutional Neural Networks (2)
This workshop will be the second lecture in our introduction to convolutional neural networks (CNNs). We will continue our learning by applying data augmentation and transfer learning techniques to improve our solution for the classic Dogs-vs-Cats problem using PyTorch. A basic understanding of the topics covered in previous sessions is assumed. Having working experience with…
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Learning Convolutional Neural Networks (1)
This workshop will provide an introduction to convolutional neural networks (CNNs). We will begin by using PyTorch to perform image processing on the classic Dogs-vs-Cats problem. Basic knowledge of the topics covered in previous sessions is assumed. Having working experience with Python, Jupyter Notebooks, and linear algebra will be helpful for fully participating in the…
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Using Jupyter From Anywhere For Free
This workshop is an overview of how to acquire and run Jupyter Notebook services for free from anywhere. In another word, you will learn how a web browser is all you need for getting free Jupyter resources. Any questions about this workshop can be emailed to Qiyang Hu at huqy@oarc.ucla.edu Presented by the Office of…
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Hoffman2 Happy Hour: Connecting to the Hoffman2 Cluster via Jupyter Notebooks + Q&A
The Hoffman2 Happy Hours are designed to showcase one cluster related topic in a short presentation (no more than 20 minutes and generally much less) or lightning talk format, to be followed by 30 to 40 minutes of discussion and user support (office hour style). Each Hoffman2 Happy Hour meeting is 50 minutes long. Bring…
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Running Applications on the Hoffman2 Cluster, Part I
Registration link: https://ucla.zoom.us/meeting/register/tJYqc-6rqz0qGdCvJuus9bUKV2xVtQHZQnHu The Hoffman2 Cluster is a powerful computational resource for the UCLA research community. This workshop is part of a three-seminar series designed to introduce users to the Hoffman2 Cluster environment and to clarify the process of porting applications or using applications already available on the cluster. It also addresses how to port…
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Using Jupyter with Hoffman2 and HPC Systems
This short class will illustrate several powerful tools and features that can enhance one’s experience with Jupyter notebooks. The interactive demonstrations will include a brief overview of plotting tools and magics, followed by demonstrations of how to make interactive widgets for interactive visualizations and dashboards and how to generate analysis pipelines and reports. Basic familiarity…
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Running Applications on the Hoffman2 Cluster: Case Studies
This class will address the process of creating Matlab standalone executables and running Matlab in batch, as well as running Abaqus python scripts. Example of how to submit array jobs using Abaqus, R and other applications. Can my simulations be submitted as array jobs? Bring your own problem. Also, Jupyter Notebooks: another way to run…
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Introduction to Jupyter
The Jupyter Notebook is a computing tool that allows users to edit and run Python, R, Julia (and many other programming languages) inside a web browser. Furthermore, it is a powerful tool that allows users to combine live code, text, and visualizations in an interactive, shareable, reproducible document. It has been growing in popularity in…
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Introduction to Jupyter
RSVP FOR EVENT The Jupyter Notebook is a computing tool that allows users to edit and run Python, R, Julia (and many other programming languages) inside a web browser. Furthermore, it is a powerful tool that allows users to combine live code, text, and visualizations in an interactive, shareable, reproducible document. It has been growing…
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