• Flexible and Robust Machine Learning Using mlr3 in R

The free online book for the mlr3 machine learning framework for R. Gives a comprehensive overview of the package and ecosystem, suitable from beginners to experts. You'll learn how to build and evaluate machine learning models, build complex machine learning pipelines, tune their performance automatically, and explain how machine learning models arrive at their predictions.

• Handwritten Digits PyTorch

This tutorial is essentially the "hello world" of image recognition and feed-forward neural network (using PyTorch). Using the MNIST database (filled within images of handwritten digits), the tutorial will instruct how to build a feed-forward neural network that can recognize handwritten digits. A solid understanding of feed-forward and back-propagation is recommended.

• DAGMan
• DAGMan Workflows

DAGMan (Directed Acyclic Graph Manager) is a meta-scheduler for HTCondor. It manages dependencies between jobs at a higher level than the HTCondor Scheduler. It is a workflow management system developed by the High-Throughput Computing (HTC) community, specifically for managing large-scale scientific computations and data analysis tasks. It enables users to define complex workflows as directed acyclic graphs (DAGs). In a DAG, nodes represent individual computational tasks, and the directed edges represent dependencies between the tasks. DAGMan manages the execution of these tasks and ensures that they are executed in the correct order based on their dependencies. The primary purpose of DAGMan is to simplify the management of large-scale computations that consist of numerous interdependent tasks. By defining the dependencies between tasks in a DAG, users can easily express the order of execution and allow DAGMan to handle the scheduling and coordination of the tasks. This simplifies the development and execution of complex scientific workflows, making it easier to manage and track the progress of computations.

• Application Fundamentals

The provided text discusses various aspects of Android app development fundamentals. It covers key concepts related to app components, the AndroidManifest.xml file, and app resources. Android apps are built using various components, including Activities, Services, Broadcast Receivers, and Content Providers. These components serve different purposes and have distinct lifecycles. Activities are used for user interaction, services for background tasks, broadcast receivers for system-wide event handling, and content providers for managing shared data.The AndroidManifest.xml file is essential for declaring app components, permissions, and other settings. It informs the Android system about the app's components and capabilities. For instance, it specifies the minimum API level, declares hardware and software requirements, and defines intent filters to enable components to respond to specific actions.It's crucial to declare app requirements, such as device features and minimum Android API levels, to ensure compatibility with different devices and configurations. These declarations help in filtering the app's availability on Google Play for users with compatible devices.Android apps rely on resources separate from code, including images, layouts, strings, and more. These resources are stored in various directories and can be tailored for different device configurations. Providing alternative resources allows for optimization across different languages, screen sizes, orientations, and other factors. Understanding these fundamentals is essential for developing Android applications effectively, ensuring compatibility, and providing a consistent user experience across a wide range of devices and configurations.

• An Introduction to Julia
• The Julia Computing Language

The Julia Programming Language is one of the fastest growing software languages for AI/ML development. It writes in manner that's similar to Python while being nearly as fast as C++, while being open source, and reproducible across platforms and environments. The following link provide an introduction to using Julia including the basic syntax, data structures, key functions, and a few key packages.

• CS224N: NLP with Deep Learning

CS244N is a renowned natural language processing course offered by Stanford University and taught by Christopher Manning. It covers a wide range of topics in NLP, including language modeling, machine translation, sentiment analysis, and more. It teaches both foundational concepts and cutting-edge research to gain a comprehensive understanding of NLP techniques and applications.

• phenoACCESS-24: Workshop on Research Computing and Plant Phenotyping

phenoACCESS-24: Workshop on Research Computing and Plant Phenotyping High-throughput plant phenotyping is computationally intensive, requiring data storage, data processing and analysis, research computing expertise, and mechanisms for data sharing. This workshop is aimed at research computing workforce development by addressing questions such as what is plant phenotyping; what types of data are collected; what are the preprocessing and analytical needs; what tools and platforms exist for data capture, management, analysis, and storage; and how best to collaborate and engage with phenotyping researchers. The full-day agenda will include speakers (scientists and research compute staff); panel discussions (how to work with research computing staff and facilities; how to engage with phenotyping scientists), and networking opportunities (meet-and-greet, ice breakers, small group discussions). The videos and slide decks for the talks are included on the linked page.

• Neurostars

A question and answer forum for neuroscience researchers, infrastructure providers and software developers.

• What is VPN? How It Works, Types of VPN

A VPN, or Virtual Private Network, is a technology that creates a secure tunnel between your device and a VPN server. This tunnel encrypts all of your traffic, making it unreadable to anyone who tries to intercept it.

• CMake Tutorials

CMake is an open-source tool used to manage the build process in operating systems. This tutorial takes you through how to use CMake from the very basics with example projects.

tutorial on introduction to making a AI Chat assistant using GenAI API

• OLCF User Training Main Site
• OLCF Training Calendar
• OLCF Training Archive
• OLCF Training Github

Upcoming training events and archives of training materials detailing general HPC best practices as well as how to use OLCF resources and services.

• Pip Guide

pip stands for "pip installs packages". It's the go-to package manager for Python, allowing developers to install, update, and manage software libraries and dependencies used in Python projects. With just a few commands in your terminal or command prompt, pip makes it effortless to fetch libraries from the Python Package Index (PyPI) and integrate them into your projects. This guide will walk you through the basics of pip, from installation to advanced package management.

• Discover Data Science

Discover Data Science is all about making connections between prospective students and educational opportunities in an exciting new, hot, and growing field – data science.

• CaRCC

CaRCC – the Campus Research Computing Consortium – is an organization of dedicated professionals developing, advocating for, and advancing campus research computing and data and associated professions. Vision: CaRCC advances the frontiers of research by improving the effectiveness of research computing and data (RCD) professionals, including their career development and visibility, and their ability to deliver services and resources for researchers. CaRCC connects RCD professionals and organizations around common objectives to increase knowledge sharing and enable continuous innovation in research computing and data capabilities.

• R for Research Scientists GitHub Repository

A book for researchers who contribute code to R projects: This booklet is the result of my work with the Social Cognition for Social Justice lab. It was developed in response to questions I was getting from students; both grad students that were making software design decisions, and undergraduates who were using things like version control for the first time. Although many tutorials and resources exist for these topics, there was not a single source that I thought covered just enough material to build up to the workflow used by the lab without extraneous detail.

• TrustedCI Open Ondemand 2021 Audit

Open OnDemand has been audited by Trusted CI, the NSF Cybersecurity Center of Excellence, to enhance its security and maintain its status as a trusted platform, with the latest engagement report contributing to ongoing security improvements. Trusted CI's mission is to provide the NSF community with a clear understanding of cybersecurity, its significance to computational science, and the necessary steps to establish and sustain an effective cybersecurity program.

• https://womeninhpc.org

Through collaboration and networking, WHPC strives to bring together women in HPC and technical computing while encouraging women to engage in outreach activities and improve the visibility of inspirational role models.

• https://lectures.scientific-python.org/

Comprehensive tutorials and lecture notes covering various aspects of scientific computing using Python and Scipy.

• The GitHub that contains the library itself, and examples
• Library documentation

JSON is a lightweight format for storing and transporting data, for example in a config file. This library is header-only, and has easy-to-read documentation. It is a C++ library.

• CUDA Toolkit Documentation

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

• EasyBuild Documentation
• EasyConfigs Repository

EasyBuild is a software installation framework that allows administrators to easily build and install software on high-performance computing (HPC) systems. It supports a wide range of software packages, toolchains, and compilers. Supported software are found in the EasyConfigs repository, one of several resositories in EasyBuild project.

• Python Courses Online

Learn Python online with these distance learning courses.

• Active Inference: The Free Energy Principle in Mind, Brain, and Behavior

This textbook is the first comprehensive treatment of active inference, an integrative perspective on brain, cognition, and behavior used across multiple disciplines including computational neurosciences, machine learning, artificial intelligence, and robotics. It was published in 2022 and it's open access at this time. The contents in this textbook should be educational to those who want to understand how the free energy principle is applied to the normative behavior of living organisms and who want to widen their knowledge of sequential decision making under uncertainty.

• Docker Documentation

Docker allows for containerization of any task - basically a smaller, scalable version of a virtual machine. This is very useful when transferring work across computing environments, as it ensures reproducibility.