Search Results for "computing" - Page 6
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829 projects for "computing" with 1 filter applied:
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Save Up to 91% on Cloud Compute With Spot VMsRun batch jobs at 60-91% off with Spot VMs. Long-running workloads get automatic discounts with sustained use.
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Earn up to 16% annual interest with Nexo.Generate interest, borrow against your crypto, and trade a range of cryptocurrencies — all in one platform. Geographic restrictions, eligibility, and terms apply.
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spark-ml-source-analysis
Spark ml algorithm principle analysis and specific source code
...The repository contains detailed analyses of various algorithms including classification, regression, clustering, dimensionality reduction, and recommendation systems. Each section discusses both the mathematical principles behind the algorithms and how Spark implements them in a distributed computing environment. By studying these implementations, readers gain insight into how large-scale machine learning pipelines operate across distributed data systems. -
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data-science-ipython-notebooks
Data science Python notebooks: Deep learning
...Many notebooks introduce concepts step by step, then apply them to real datasets so readers can see techniques in action. Advanced sections touch on neural networks and distributed computing topics, helping you bridge from basics to production-adjacent workflows. The collection is suitable for self-paced study, quick reference, or as teaching materials in workshops. By combining narrative explanations with executable code, it shortens the path from theory to working prototypes. -
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numpy_exercises
Numpy exercises
numpy_exercises is a collection of short practice problems designed to teach numerical computing through individual NumPy functions. The material is organized as Jupyter notebooks so learners can work interactively and compare their answers with companion solution notebooks. Exercises cover array creation, manipulation, string operations, help utilities, input and output, and linear algebra. Additional sections address discrete Fourier transforms, logic functions, mathematics, random sampling, and set routines. ... -
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Python Data Science Tutorials
Common data analysis and machine learning tasks using python
...It combines external tutorials, courses, reference guides, notebooks, articles, and selected code examples. The collection begins with Python fundamentals and then moves into scientific computing, statistics, NumPy, pandas, data exploration, and visualization. Its machine learning sections cover practical algorithms and libraries, including regression, classification, clustering, support vector machines, and computer vision resources. Additional material addresses text mining, sentiment analysis, serialization with pickle, AutoML, regular expressions, and web scraping. ... -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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AnharmoniCAOS
Cagliari-Orsay model for anharmonic molecular spectra in 2nd order PT
Given dynamical coefficients and/or derivatives of the ionic potential with respect to normal (harmonic) vibrational modes, compute anharmonic energies and electric dipole-permitted transitions and intensities using nearly-degenerate perturbation theory (i.e. properly accounting for Fermi and Darling-Dennison resonances). -
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Functional, Data Science Intro To Python
[tutorial]A functional, Data Science focused introduction to Python
...The sections after that, involve varying levels of difficulty and cover topics as diverse as Machine Learning, Linear Optimization, build systems, command line tools, recommendation engines, Sentiment Analysis and Cloud Computing. -
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Jadex is a Belief Desire Intention (BDI) reasoning engine that allows for programming intelligent software agents in XML and Java. The resoning engine is very flexible.
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Avian Parallel Computing
Develop parallel programs. Try various thread configs. GUI front-end.
Avian Computing seeks to efficiently create parallel programs by changing how we think about parallel programs. Avian Computing discourages thinking about lines of code and encourages us to use a new model: flocks of birds. Changing the model to flocks of birds makes it easier to think about the actions that we want to perform concurrently, which leads to simpler and quicker development of working parallel programs. -
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Python/xarray tutorial
Python/xarray tutorial for GEOS-Chem users
If the page is loaded successfully, you should see a Jupyter notebook interface. Then, click on the first notebook to get started. Jupyter combines Python code, execution results, plots, custom texts, and even Latex formulas in a single page. Besides using the Jupyter program, you can also view the static notebook on GitHub (e.g the first notebook). Python is free & open-source so can be easily installed on any machines. To best way to get the scientific Python environment is using the Conda... -
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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Incanter
Clojure-based, R-like statistical computing and graphics environment
Incanter is a Clojure-based, R-like statistical computing and visualization library running on the JVM. It integrates core numerical libraries like Parallel Colt and JFreeChart to deliver data manipulation, modeling, statistical tests, and charting in a REPL-friendly environment. Start by visiting the Incanter website for an overview, check out the documentation page for a listing of HOW-TOs and examples, and then download either an Incanter executable or a pre-built version of the latest build of Incanter, which includes all the necessary dependencies, and unpack the file (if you would like to build it from source, read Building Incanter). ... -
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JPPF
The open source grid computing solution
JPPF makes it easy to parallelize computationally intensive tasks and execute them on a Grid. -
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ProbAbilistic CALculator - a package for computing with probability distributions
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Madara
Middleware for distributed applications
The purpose of the project is to develop a portable programming framework that facilitates distributed and multi-threaded programming for C++, Java, and Python. MADARA was originally developed as an agent-based middleware specifically for real-time, distributed artificial intelligence, but is now more general purpose for distributed timing, control, knowledge and reasoning, and quality-of-service. MADARA is composed of several tools and middleware, and the main entry point into the system... -
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A framework to run MATLAB programs as batch jobs. Features a structured input description, integrity constraints and GUI.Independent parts of a job can execute in parallel on a cluster computer. Developed at Freiburg Brain Imaging (FBI) - http://fbi.uniklinik-freiburg.de/
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Prolog+CG is a Java implementation of Prolog with extensions implementing a subset of the Conceptual Graph (CG) theory of John Sowa. CGs are first-class datatypes on a par with terms. Object oriented extensions are also included.
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PixelFlow
A Processing/Java library for high performance GPU-Computing (GLSL)
PixelFlow is a Processing library focused on advanced graphics and visual effects, offering an extensive suite of GPU-based tools for visual artists, researchers, and creative coders. It enables real-time simulation and rendering of complex effects such as fluid dynamics, reaction-diffusion systems, soft shadows, and more, all powered by GLSL shaders. Its modular structure allows for chaining and composing various visual effects easily, making it ideal for installations, performances, and... -
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Collaborative Computing Project for NMR
Collaborative Computing Project for NMR (CCPN)
The Collaborative Computational Project for NMR (CCPN) provides tools and knowledge to maximise the impact of the biological NMR studies. The CCPN software facilitates data analysis and software integration. The project actively promotes the exchange of knowledge and provides training and best practices for the NMR community. CCPN also has a leading role in the development of a NMR data-sharing standard and coordination of NMR instrumentation proposals for RCUK and BIS. The 28 partners of... -
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A Whirlwind Tour of Python
The Jupyter Notebooks behind my OReilly report
A Whirlwind Tour of Python is a concise but fast-paced introduction to core Python concepts, created by Jake VanderPlas as a companion to his work in scientific computing and data science. It consists of a series of Jupyter notebooks that walk through syntax, semantics, control flow, data structures, functions, errors, iterators, list comprehensions, generators, modules, strings, regular expressions, and a short preview of data science tools. The material is aimed at people who already know how to program in another language and want to transition efficiently into idiomatic Python, particularly for research and analytical work. ... -
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DMTK
Microsoft Distributed Machine Learning Toolkit
The Microsoft Distributed Machine Learning Toolkit (DMTK) is an open-source framework created to support scalable machine learning across distributed computing environments. Developed by Microsoft Research, the toolkit provides infrastructure and algorithms designed to train large models efficiently on clusters of machines rather than a single system. At its core is a parameter-server architecture called Multiverso, which manages model parameters and synchronizes updates across distributed training processes. ... -
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The Node Director is a tool for managing distributed, hetergeneous UNIX Systems. Its functionality includes System Configuration, Application Distribution, NIS & NIS+ Management, User Creation and Dynamic System Documentation.
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Recursive computing and matching of Context Triggered Piecewise Hashing (aka Fuzzy Hashing). Supports Windows, *nix, BSD, OS X, etc.
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asyncoro
Python framework for asynchronous, concurrent, distributed programming
asyncoro is a Python framework for developing concurrent, distributed, network programs with asynchronous completions and coroutines. Asynchronous completions implemented in asyncoro are sockets (non-blocking sockets), database cursors, sleep timers and locking primitives. Programs developed with asyncoro have same logic and structure as Python programs with threads, except for a few syntactic changes. asyncoro supports socket I/O notification mechanisms epoll, kqueue, /dev/poll (and poll... -
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SmartFrog (Smart Framework for Object Groups) is a framework for configuring and automatically activating distributed applications. The SmartFrog framework is released under LGPL license. More info at: www.smartfrog.org
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H2O-3
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning
H2O-3 is an open-source machine learning platform designed to build scalable and distributed machine learning models across large datasets. The system operates as an in-memory computing platform that allows data scientists to train models quickly using distributed resources. It supports many machine learning algorithms including generalized linear models, gradient boosting machines, deep learning networks, and ensemble techniques. The platform provides interfaces for multiple programming languages such as Python, R, Java, and Scala, making it accessible to a wide range of developers and data scientists. ... -
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jdds
An Implementation of Java5 PSM for DDS
jdds is an implementation of Java5 PSM for DDS defined by OMG
