Useful R Packages for Data Science and Statistics
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This Udacity article listed the most frequently used R packages for data science and statistics. For each package, the article provided the link to its official documentation. It will be a great start point if you want to start your data science journey in R.
DARWIN Documentation Pages
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DARWIN (Delaware Advanced Research Workforce and Innovation Network) is a big data and high performance computing system designed to catalyze Delaware research and education
ACCESS Pegasus Documentation
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The documentation provides an overview of using Pegasus, a workflow management system, on ACCESS resources for high throughput computing (HTC) workloads, covering logging in, workflow creation, resource configuration, and monitoring options.
PyTorch for Deep Learning and Natural Language Processing
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PyTorch is a Python library that supports accelerated GPU processing for Machine Learning and Deep Learning. In this tutorial, I will teach the basics of PyTorch from scratch. I will then explore how to use it for some ML projects such as Neural Networks, Multi-layer perceptrons (MLPs), Sentiment analysis with RNN, and Image Classification with CNN.
Data Visualization tools for Python
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Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. It makes analyzing and presenting your data extremely easy and works with Python which many people already know.
GIS: Geocoding Services
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Geocoding is the process of taking a street address and converting it into coordinates that can be plotted on a map. This conversion typically requires an API call to a remote server hosted by an organization/institution. The remote server will take the address attributes provided by you and the remote server will compare it to the data it contains and return a best estimate on the coordinates for that location.
There are many geocoding services available with different world coverages, quality of result, and set different rate limits for access. For R, a package called "tidygeocoder" provides an easy way to connect to these different services. As an additional benefit, their documentation provides a good summary of geocoding services available and links to their documentation. The link to the documentation for gecoding services accessible by "tidygeocoder" is provided below.
For Python, geopy package is a library that provides connection to various geocoding services. The link to the documentation for this package is also included below.
Introduction to Python for Digital Humanities and Computational Research
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This documentation contains introductory material on Python Programming for Digital Humanities and Computational Research. This can be a go-to material for a beginner trying to learn Python programming and for anyone wanting a Python refresher.
Fairness and Machine Learning
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The "Fairness and Machine Learning" book offers a rigorous exploration of fairness in ML and is suitable for researchers, practitioners, and anyone interested in understanding the complexities and implications of fairness in machine learning.
Numba: Compiler for Python
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Numba is a Python compiler designed for accelerating numerical and array operations, enabling users to enhance their application's performance by writing high-performance functions in Python itself. It utilizes LLVM to transform pure Python code into optimized machine code, achieving speeds comparable to languages like C, C++, and Fortran. Noteworthy features include dynamic code generation during import or runtime, support for both CPU and GPU hardware, and seamless integration with the Python scientific software ecosystem, particularly Numpy.
AHPCC documentary
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This link is a documentary website to use AHPCC.
Intro to Statistical Computing with Stan
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The Stan language is used to specify a (Bayesian) statistical model with an imperative program calculating the log probability density function. Here are some useful links to start your exploration of this statistical programming language, and a Python interface to Stan.
Intro to Machine Learning on HPC
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This tutorial introduces machine learning on high performance computing (HPC) clusters. While it focuses on the HPC clusters at The University of Arizona, the content is generic enough that it can be used by students from other institutions.
Jetstream2 Docs Site
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Jetstream2 makes cutting-edge high-performance computing and software easy to use for your research regardless of your project’s scale—even if you have limited experience with supercomputing systems.Cloud-based and on-demand, the 24/7 system includes discipline-specific apps. You can even create virtual machines that look and feel like your lab workstation or home machine, with thousands of times the computing power.
Introductory Tutorial to Numpy and Pandas for Data Analysis
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In this tutorial, I present an overview with many examples of the use of Numpy and Pandas for data analysis. Beginners in the field of data analysis can find It incredibly helpful, and at the same time, anyone who already has experience in data analysis and needs a refresher can find value in it. I discuss the use of Numpy for analyzing 1D and 2D multidimensional data and an introduction on using Pandas to manipulate CSV files.
Chameleon
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Chameleon is an NSF-funded testbed system for Computer Science experimentation. It is designed to be deeply reconfigurable, with a wide variety of capabilities for researching systems, networking, distributed and cluster computing and security.
Official Documentation of VisIt
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VisIt is a prominent open-source, interactive parallel visualization and graphical analysis tool predominantly used for viewing scientific data. Its GitHub repository offers a detailed insight into the software's source code, documentation, and contribution guidelines. In particular, it offers useful examples on how it
ACCESS KB Guide - Anvil
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Purdue University is the home of Anvil, a powerful supercomputer that provides advanced computing capabilities to support a wide range of computational and data-intensive research spanning from traditional high-performance computing to modern artificial intelligence applications.
Info about retiring of R GIS packages rgdal, rgeos, maptools in 2023
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R GIS packages "rgdal", "rgeos", and "maptools" are package set to be archived and no longer supported by end of 2023. Many other R GIS packages are build on top of these packages, including "sp" and "raster". The packages recommended as replacement for "sp" is "sf" and the replacement for "raster" is "terra". Below are links to published articles regarding this transition. Additionally, I am including links to the documentation for the new packages recommended to be used "sf" and "terra".
CUDA Toolkit Documentation
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NVIDIA CUDA Toolkit Documentation: If you are working with GPUs in HPC, the NVIDIA CUDA Toolkit is essential. You can access the CUDA Toolkit documentation, including programming guides and API references, at this provided website
Bioinformatics Workflow Management with Nextflow
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Nextflow is an open-source, domain-specific language and workflow manager designed for the execution and coordination of scientific and data-intensive computational workflows. It was specifically created to address the challenges faced by researchers and scientists when dealing with complex and scalable computational pipelines, particularly in fields such as bioinformatics, genomics, and data analysis.
Here provided some links to start with.
ACCESS Guide (originally given at Duke OIT)
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A guide for Duke OIT on how to advise users on using ACCESS and allocation credits to jetstream 2 for Duke University members. This can be used for non Duke members. Assumes the reader has basic knowledge of ACCESS.
Globus Documentation
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Globus is a data transfer, sharing, automation, and discovery service used by hundreds of thousands of researchers to manage "big data" at universities, research labs, and national systems such as ACCESS. The Globus documentation website provides how-to guides, reference documentation, and examples for Globus's web application, command-line interface, Python software development kit (SDK), and APIs.
The Official Documentation of Pandas
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Pandas is one of the most essential Python libraries for data analysis and manipulation. It provides high-performance, easy-to-use data structures, and data analysis tools for the Python programming language. The official documentation serves as an in-depth guide to using this powerful tool including explanations and examples.
ACCESS KB Guide - DELTA
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NCSA is the home of Delta, a computing and data resource that balances cutting-edge graphics processor and CPU architectures with a non-POSIX file system with a POSIX-like interface. Delta allows applications to reap the benefits of modern file systems without rewriting code.
Probabilistic Semantic Data Association for Collaborative Human-Robot Sensing
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Humans cannot always be treated as oracles for collaborative sensing. Robots thus need to maintain beliefs over unknown world states when receiving semantic data from humans, as well as account for possible discrepancies between human-provided data and these beliefs. To this end, this paper introduces the problem of semantic data association (SDA) in relation to conventional data association problems for sensor fusion. It then, develops a novel probabilistic semantic data association (PSDA) algorithm to rigorously address SDA in general settings. Simulations of a multi-object search task show that PSDA enables robust collaborative state estimation under a wide range of conditions.