We will give a general introduction to PyTorch, a popular deep learning framework, with practical illustrations on the primary usage of tensors and automatic differentiation, and on solving a simple temperature-conversion problem using PyTorch. The knowledge of topics covered in the previous session about machine/deep learning is assumed. Working experience with Python and Jupyter Notebooks…
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Python
Big Data on HPC
This workshop will go over using Big Data techniques on HPC resources. Big Data methods are used when data size because so large, it becomes challenging to compute. Also, when machine learning models become so complex, it can also be challenging to train. In this workshop, we will go over examples of solving Big Data…
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High Performance Machine Learning Using Scikit-Learn
As machine learning gains more and more popularity in science and technology in recent years, scikit-learn becomes one of the must-have libraries in the general machine learning toolbox. In this lecture we will discuss some advanced topic on using scikit-learn python library to make high performance machine learning, specifically the speedup modeling using multicore and…
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Learning Scikit-Learn
As machine learning gains more and more popularity in science and technology in recent years, scikit-learn becomes one of the must-have libraries in the general machine learning toolbox. In this lecture we will present an introduction about the basics of scikit-learn python library. Prerequisite knowledge for the workshop includes Python programming and basic machine learning…
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Hoffman2 Happy Hour: Using Anaconda on Hoffman2
Anaconda (https://www.anaconda.com/) is a distribution of R and Python that can be used to easily install many popular data science, biostats, and other packages. This Hoffman2 Happy Hour will go discus using Anaconda on Hoffman2. This can be applied to using Anaconda on various other HPC resources. We will go over creating conda environments and…
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Boosting Python for High Performance Data Analytics (2) DataFrame Game
While Python becomes the most popular programming language since 2019, data scientists often have a few common complaints about its slow speed and the limited capabilities of handling the big data scenarios. In this workshop series, we will present an extensive discussion on how to improve the performance of Python in data science by looking…
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Data Visualization with Python II: Making Interactive Plots and Widgets
Python is a very popular language for computational and data science, and it has many powerful capabilities for visualizing data. Data visualization plays an essential role in representing data so that its underlying patterns might be conveyed and understood. The second part of this series will explore various ways that Python can be used to…
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Boosting Python for High Performance Data Analytics (1) Interpreter War
While Python becomes the most popular programming language since 2019, data scientists often have a few common complaints about its slow speed and the limited capabilities of handling the big data scenarios. In this workshop series, we will present an extensive discussion on how to improve the performance of Python in data science by looking…
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Using Container on HPC resources
This workshop will go over how to use container on HPC resources. Containers are a great way to run scientific software on various HPC platforms. Users can create a ‘virtual’ OS to easily install any application and transfer it to any system with container software. This workshop will cover how to build and use containers…
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Running Applications on the Hoffman2 Cluster, Part II
Registration link: https://ucla.zoom.us/meeting/register/tJIvd-igpjMiGNVkod90GFNhBTuT7pwRfj5- 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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