Search Results for "source" - Page 4
Sort By:
Showing 113 open source projects for "source"
View related business solutions-
Gemini 3 and 200+ AI Models on One PlatformBuild, govern, and optimize agents and models with Gemini Enterprise Agent Platform.
-
Full-stack observability with actually useful AI | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
-
1
hui
hewies user interface - 3D scientific visualisation tool
Python project with goal to provide FOSS library to extract, analyse and visualise data in a 3D fashion. The instance will connect to a data source, ods sheet, csv, sql DB, pyodbc the instance will analyse and/or transform the data to be presented to the visualisation functionality the instance will visualise the data in a 3D fashion, likely using third party FOSS -
2
Scripting Language Bindings
A port of WFOPT to the several scripting languages
This project contains bindings for various scripting languages to the Wheefun Options Parsing Library. It is meant to provide parity with the C implementation so .NET languages can take advantage of WFOPT. For more information, please see the main page. -
3
OmicSelector
Feature selection and deep learning modeling for omic biomarker study
OmicSelector is an environment, Docker-based web application, and R package for biomarker signature selection (feature selection) from high-throughput experiments and others. It was initially developed for miRNA-seq (small RNA, smRNA-seq; hence the name was miRNAselector), RNA-seq and qPCR, but can be applied for every problem where numeric features should be selected to counteract overfitting of the models. Using our tool, you can choose features, like miRNAs, with the most significant... -
4
mlr
Machine Learning in R
R does not define a standardized interface for its machine-learning algorithms. Therefore, for any non-trivial experiments, you need to write lengthy, tedious, and error-prone wrappers to call the different algorithms and unify their respective output. {mlr} provides this infrastructure so that you can focus on your experiments! The framework provides supervised methods like classification, regression, and survival analysis along with their corresponding evaluation and optimization methods,... -
$300 in Free Credit Towards Top Cloud ServicesStart your project in minutes. After credits run out, 20+ products include free monthly usage. Only pay when you're ready to scale.
-
5
geocompr
Geocomputation with R: an open source book
This repository hosts the source for Geocomputation with R, an open-source book covering spatial data analysis, visualization, and modeling using R. It teaches how to work with vector and raster data, coordinate systems, mapping, and geocomputation techniques using packages like sf, terra, tmap, and more. Actively maintained and updated for real-world geospatial workflows. -
6
Data Analysis for the Life Sciences
Rmd source files for the HarvardX series PH525x
This repository holds the R Markdown (.Rmd) source files for the PH525x / HarvardX course series (Data Analysis for the Life Sciences / Genomics) managed by GenomicsClass. It functions as the canonical source for course lab exercises, lecture modules, and reading materials in reproducible format. Students and learners use these R Markdown files to follow along, knit notebooks, run code samples, and complete the lab-based assignments. -
7
osm4scala
Reading OpenStreetMap Pbf files.
Scala and polyglot Spark library (Scala, PySpark, SparkSQL, ... ) focused on reading OpenStreetMap Pbf files. -
8
generativeart
Create Generative Art with R
generativeart is an R package for creating algorithmic art by computing the positions of many thousands of points according to user-defined mathematical formulas with randomized parameters. Each render uses a seed to introduce controlled randomness, so every image is unique while remaining reproducible when the same seed and formula are reused. The package logs the seed, formula, and file name to a CSV, which makes it easy to catalog outputs, re-generate favorites, and track experiments. A... -
9
miRPV
miRPV: An automated pipeline for miRNA Prediction and Validation in si
miRPV is an Automated tool that allows users to predict and validate microRNA from genome/gene sequence. System Requirement CPU: AMD64 (64bit) Memory: 2Gb RAM Storage: 5Gb Ubuntu 18.04 -
Earn up to 16% annual interest with Nexo.Put idle assets to work with competitive interest rates, borrow without selling, and trade with precision. All in one platform. Geographic restrictions, eligibility, and terms apply.
-
10
Covidex
Ultra fast and accurate subtyping tool of viral genomes.
Viral subtypes or clades represent clusters among isolates from the global population of a defined species. Subtypification is relevant for studies on virus epidemiology, evolution and pathogenesis. In this sense, Covidex was developed as an open source alignment-free machine learning subtyping tool. It is a shiny app that allows fast and accurate classification of viral genomes in pre-defined clusters. If more than 1000 sequences are loaded the tool will run in multithread mode. Capable of classifying 16000 genome sequences in less than a minute (AMD Ryzen 7 1700 8-core Processor 3 GHz) For a Web-based version of the app (only for small datasets: 100 seqs max) please go to http://covidex.unlu.edu.ar If you use Covidex please consider citing the following preprint: https://biorxiv.org/cgi/content/short/2020.08.21.261347v1 If you think my work is useful you can buy me a coffee! ... -
11
rethinking
Statistical Rethinking course and book package
This R package accompanies Richard McElreath’s Statistical Rethinking (2nd edition), offering utilities to fit and compare Bayesian models using both MAP estimation (quap) and Hamiltonian Monte Carlo via RStan (ulam). It supports specifying models via explicit distributional assumptions, providing flexibility for advanced statistical workflows. -
12
stat-cookbook
The probability and statistics cookbook
A compact “Probability and Statistics Cookbook” offering concise mathematical recipes for key statistical concepts—expectation, variance, distributions and inequalities—packaged as LaTeX and R-based executable documents. -
13
QuantifyPoly(A)
Quantification of poly(A) sites from 3' end sequencing data
QuantifyPoly(A) - a tool for quantification of poly(A) sites from 3' end sequencing data. [1] QuantifyPoly(A) user manual Please visit the Wiki page of this website. [2] QuantifyPoly(A) Q&A For Q&A, please visit the Blog page of this website. [3] QuantifyPoly(A) bug report You can report a bug as a Ticket request, or start a topic session in the Discussion webpage of this website. -
14
covid19model
Code for modelling estimated deaths and cases for COVID19
Code for modeling estimated deaths and infections for COVID-19 from "Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe", Flaxman, Mishra, Gandy et al, Nature, 2020, the published version of our original Report 13. This is the release related to our Tiers paper, where we use the latent factor model to estimate the effectiveness of tiers systems in England. Peer-reviewed version is to be out soon. All other code is still the same for previous releases. The code... -
15
MitoSAlt
Identification of mitochondrial structural alterations
MitoSAlt is a pipeline to identify large deletions and duplications in human and mouse mitochondrial genomes from next generation whole genome/exome sequencing data. The pipeline is capable of analyzing any circular genome in principle, as long as a proper configuration file is provided. -
16
R4DS (R for Data Science)
R for data science: a book
“R for Data Science” (r4ds) is the source material (book + examples) by Hadley Wickham et al., intended to teach data science using R and the tidyverse. It covers the workflow from importing data, tidying, transforming, visualizing, modelling, communicating results, and programming in R. The repository contains the source files (Quarto / RMarkdown), example datasets, visualizations, exercises, and all content needed to build the book. -
17
Pain2D are programs which were developed for the automated pain drawing collection and classification of diseases on the basis of pain drawings in pen-and-paper and digital form for research purposes. Pain2D is currently not a diagnostic tool, but is aimed at scientists, physicians and anyone interested in the automated analysis of pain drawings.
-
18
Reproducible-research
A Reproducible Data Analysis Workflow with R Markdown, Git, Make, etc.
In this tutorial, we describe a workflow to ensure long-term reproducibility of R-based data analyses. The workflow leverages established tools and practices from software engineering. It combines the benefits of various open-source software tools including R Markdown, Git, Make, and Docker, whose interplay ensures seamless integration of version management, dynamic report generation conforming to various journal styles, and full cross-platform and long-term computational reproducibility. The workflow ensures meeting the primary goals that 1) the reporting of statistical results is consistent with the actual statistical results (dynamic report generation), 2) the analysis exactly reproduces at a later point in time even if the computing platform or software is changed (computational reproducibility), and 3) changes at any time (during development and post-publication) are tracked, tagged, and documented while earlier versions of both data and code remain accessible. -
19
yabasta
Yet Another BAsic Scraper and Text Analysis
YA BASTA! is a Python/R application for Lyrics Web Scraper and Text Analysis. Web scraping is developed in Python, text analysis in R as Python subprocesses. YA BASTA! is only tested on windows OS. To run YA BASTA! just type on window command prompt: python.exe yabasta.py -
20
hrbrthemes
Opinionated, typographic-centric ggplot2 themes and theme components
hrbrthemes is a focused ggplot2 theme package with an emphasis on typography, layout precision, and visual polish. It includes themes like theme_ipsum and Font scales tailored for clean, high‑quality production graphics. -
21
Harmony Data Integration
Fast, sensitive and accurate integration of single-cell data
Harmony is a general-purpose R package with an efficient algorithm for integrating multiple data sets. It is especially useful for large single-cell datasets such as single-cell RNA-seq. Harmony has been tested on R versions =4. Please consult the DESCRIPTION file for more details on required R packages. Harmony has been tested on Linux, OS X, and Windows platforms. -
22
swirl
Learn R, in R
swirl is an R package that allows interactive, in-R learning of statistics, data science, R programming etc. The idea is that you load swirl in R, and it presents you with lessons (within R’s console or RStudio) that ask you to type commands, check results, and progress through tutorial material—without leaving the R environment. It is used for teaching R, especially for beginners, as well as for self-paced learning of packages, data manipulation, visualization, etc. Lessons and content are... -
23
posterdown
Use RMarkdown to generate PDF Conference Posters via HTML
...The rest of this example poster will show how you can insert typical conference poster features into your own document. Posterdown was created as a proof-of-concept (to myself) that it is possible to make a beautiful poster using open-source reproducible code. -
24
benchm-ml
A benchmark of commonly used open source implementations
This repository is designed to provide a minimal benchmark framework comparing commonly used machine learning libraries in terms of scalability, speed, and classification accuracy. The focus is on binary classification tasks without missing data, where inputs can be numeric or categorical (after one-hot encoding). It targets large scale settings by varying the number of observations (n) up to millions and the number of features (after expansion) to about a thousand, to stress test different... -
25
Open Intro Statistics
An open-source textbook written at the college level
OpenIntro Statistics is a dynamic take on the traditional curriculum, being successfully used at Community Colleges to the Ivy League. Each chapter's content is in one of the eight chapter folders that start with "ch_". Within each folder, there is a "figures" folder and a "TeX" folder. The TeX folder contains the text files that are used to typeset the chapters in the textbook. In many cases, R code is supplied with figures to regenerate the figure. It will often be necessary to install the...
