The term "data science" has become a ubiquitous and all-encompassing term to address any field that utilizes data analytics in one form or another. Despite having such a broad mandate, certain elements remain consistent in the approach to data science that are interdisciplinary: data acquisition, data exploration, data modeling, and data communication. In this two-part...
Anaconda is a popular, free, and open-source distribution of Python and R packages for scientific computing and data analysis. Many users prefer using Anaconda on the personal computer instead of manually installing individual packages not only for convenience but also for taking advantage of Anaconda's ability to resolve version conflicts and package dependencies. On the...
REGISTRATION IS NOW OPEN, RSVP HERE! Wednesday October 28th, 10am (PDT): Welcome message and humanitarian map training Thursday October 29th: Continue mapping and a day of workshops9am Open Street Map with Python 11am Open Data and Tableau 1pm GIS with R 3pm Introduction to QGIS Friday October 30th, 10am (PDT): Wrap-up and closing Keynote with...
Please RVSP here. Workshop will be conducted in Zoom in PST time. Invites are sent out the day before the workshop. This workshop is part one of a four-part workshop series in the 4th Annual UCLA/USC Humanitarian Mapathon. You will learn how to use Python within Jupyter Notebooks to find Open Street Map data for...
Python is a general-purpose programming language that is easy to learn and widely used. It is one of the primary programming languages for data science, and when combined with its modules such as NumPy, SciPy, Matplotlib, and Pandas, it can be a very powerful tool for numerical computing. The first part of this hands-on series...
Python is a general-purpose programming language that is easy to learn and widely used. It is one of the primary programming languages for data science, and when combined with its modules such as NumPy, SciPy, Matplotlib, and Pandas, it can be a very powerful tool for numerical computing. The second part of this hands-on series...
Python is a general-purpose programming language that is easy to learn and widely used. It is one of the primary programming languages for data science, and when combined with its modules such as NumPy, SciPy, Matplotlib, and Pandas, it can be a very powerful tool for numerical computing. The third part of this hands-on series...
Please REGISTER in advance here. Workshop will be conducted in Zoom in PST time. Invites are sent out the day before the workshop. In this hands on workshop, you will be provided with a Jupyter Notebook workspace to import census data, explore, clean, and prepare the data for analysis using python. You will also 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 in-depth introduction to scikit-learn python library. Prerequisite knowledge for the workshop includes Python programming and basic machine learning concepts.
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 first part of this series will showcase various ways that Python can be used for...
Registration link: https://ucla.zoom.us/meeting/register/tJwkdu6hqj4sG9ZioB0tM8VuXxA44AWGc6W- Visual interpretations are meaningful ways to determine spatial trends in our data. However, underlying factors—such as inconsistent geographies, scale, data gaps, overlapping data—have the potential to produce incorrect assumptions, as valuable information may be conveniently hidden from the visual output. One way to address this issue is to amend your visual output...
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...
This workshop series will present an extensive discussion on how to improve the performance of Python in data science by looking under the hood of its language/libraries and using the technologies to make Python a practical solution for the high-performance big data analytics. In the first session, we will focus on how to boost the speed of python code in an interperter level by explaining the concepts (e.g. GIL, GIT) and introducing the packages of pypy, numba, pythran, cython etc. Although no specific prerequisite is required to attend the talk, having programming experience in Python will be helpful to fully understand the lecture content.
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 concepts.
This workshop will introduce how to use Python/matplotlib and other packages to generate data visualization and animation for publications or presentations. We will discuss plotting functions and techniques available in both Matlab and Python to handle and customize your graphics in practice. The materials include simple 2D/3D plots to present scalers and vectors, filled plots...
Landsat imagery of the 2020 Bobcat wildfire generated using Python Register here Satellites are circling our planet, allowing us to "sense" things about the Earth. It is the art and science of making measurements using sensors. Remote sensing has thus become a valuable tool in research and applications in a wide range of disciplines, such...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
Learn to use code profilers (software) to analyze a program's performance and resource usage, and to use the measurement data to guide tuning methodologies and workflows, in the context of scientific computing. Any questions about this workshop can be emailed to Shao-Ching Huang at sch@ucla.edu. Presented by the Office of Advanced Research Computing (OARC). Register here:...
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...
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...
Are you interested in the connections between people? Places? Concepts? Things? Do you want to visualize data in a way that is comprehensible to a human? Do you want to see how information flows through systems? Then network analysis is for you! This introductory workshop will introduce participants to network analysis, with an emphasis on...
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...
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...
Python is a very popular language for computational and data science, and it has many powerful capabilities for visualizing data in the pursuit of understanding and conveying underlying patterns. The first part of this series will showcase various ways that Python can be used for creating graphics, following which we’ll dive into some common Python...
Python is a very popular language for computational and data science, and it has many powerful capabilities for visualizing data in the pursuit of understanding and conveying underlying patterns. The second part of this series will explore various ways that Python can be used to make interactive graphics that enhance one's ability to explore data...
Are you interested in displaying data? Do you want to make your charts and graphs understandable? Do you want to recognize when charts, graphs, and maps are manipulating the truth? If so, this is the workshop for you! We will look at using python pandas to create graphs and charts from tabular data, and how...
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...
Machine learning has undeniably emerged as a crucial element in the field of science and technology in recent years. Consequently, mastering libraries like scikit-learn, pivotal in the arsenal of machine learning tools, is of paramount importance. This lecture is designed to provide a fundamental understanding of the scikit-learn Python library. To get the most out...
Machine learning has undeniably emerged as a crucial element in the field of science and technology in recent years. Consequently, mastering libraries like scikit-learn, pivotal in the arsenal of machine learning tools, is of paramount importance.In this session, we delve into advanced aspects of leveraging the scikit-learn Python library for high-performance machine learning. We will...
This Hoffman2 Happy Hour is designed to equip participants with the knowledge and skills to harness the power of High-Performance Computing (HPC) for data analysis. The workshop focuses on two popular programming languages, R and Python, and provides step-by-step guidance on installing essential packages for HPC environments. Participants will learn how to navigate the intricacies...
Python is a very popular language for computational and data science, and it has many powerful capabilities for visualizing data in the pursuit of understanding and conveying underlying patterns. The first part of this series will showcase various ways that Python can be used for creating graphics, following which we’ll dive into some common Python...
Network analysis allows for the modeling of connections between people, places, concepts, and entities in nearly any field of study. We can visualize, describe, and even predict these connections by treating them as data through the use of widely available and free tools. This workshop will introduce participants to the field of network analysis, with...
Python is a very popular language for computational and data science, and it has many powerful capabilities for visualizing data in the pursuit of understanding and conveying underlying patterns. The second part of this series will explore various ways that Python can be used to make interactive graphics that enhance one’s ability to explore data...
While Python has been the most popular programming language since 2019, data scientists often critique its slow speed and limited capabilities in handling big data scenarios. In this workshop series, we'll tackle how to enhance Python's performance in data science by diving deep into its workings and leveraging technologies to transform Python into an effective...
Python is a very popular language for computational and data science, and it has many powerful capabilities for visualizing data in the pursuit of understanding and conveying underlying patterns. The first part of this series will showcase various ways that Python can be used for creating graphics, following which weÕll dive into some common Python...
Python is a very popular language for computational and data science, and it has many powerful capabilities for visualizing data in the pursuit of understanding and conveying underlying patterns. The second part of this series will explore various ways that Python can be used to make interactive graphics that enhance oneÕs ability to explore data...
While Python has been the most popular programming language since 2019, data scientists often critique its slow speed and limited capabilities in handling big data scenarios. In this workshop series, we'll tackle how to enhance Python's performance in data science by diving deep into its workings and leveraging technologies to transform Python into an effective...
While Python has been the most popular programming language since 2019, data scientists often critique its slow speed and limited capabilities in handling big data scenarios. In this workshop series, we'll tackle how to enhance Python's performance in data science by diving deep into its workings and leveraging technologies to transform Python into an effective...
Machine learning has become a key element in science and technology today. Mastering libraries like scikit-learn–a vital tool for machine learning–is essential. In this workshop, you'll receive a fundamental introduction to the scikit-learn Python library. For the best experience, participants should have a working knowledge of Python and a basic understanding of machine learning concepts....
Machine learning is playing an increasingly important role in science and technology. In this advanced session, we focus on leveraging scikit-learn for high-performance machine learning. We will explore how to speed up model training using multicore processors and accelerators, as well as techniques for out-of-core learning. This workshop builds on the foundational concepts from the...
