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Showing 16 open source projects for "linux"
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Introduction to Zig
An open, technical and introductory book for the Zig programming lang
This is the official repository for the book "Introduction to Zig: a project-based Book", written by Pedro Duarte Faria. To know more about the book, check out the About this book section below. You can read the current version of the book in your web browser. The book is built using the publishing system Quarto in conjunction with a little bit of R code (zig_engine.R), which is responsible for calling the Zig compiler to compile and run the Zig code examples. -
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reprex
Render bits of R code for sharing, e.g., on GitHub or StackOverflow
reprex is an R package (from the tidyverse / Posit ecosystem) that helps users make reproducible examples (reprexes) of R code: self-contained, shareable, minimal examples capturing an issue or showing desired behavior. It formats code and its output nicely (often using Markdown or syntax appropriate to posting on forums, GitHub, StackOverflow etc.), handles dependencies, session info, etc. The goal is to make debugging, asking for help, or demonstrating code easier through rigorous... -
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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. The repo is licensed under MIT, allowing reuse and... -
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Statistics for Data Scientists
"Statistics for Data Scientists: 50 Essential Concepts"
The “statistics-for-data-scientists” repository is a pedagogical resource designed to bridge rigorous statistics theory and practical data science workflows. The code and materials are intended to help data scientists and analysts grasp statistical principles (e.g. inference, regressions, hypothesis testing, probability, confidence intervals) in contexts relevant to real data analysis tasks. The repository includes Jupyter notebooks, R scripts, worked examples, and possibly problem sets that... -
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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. -
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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... -
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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. Includes many example datasets, diagrams, code samples,... -
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palmerpenguins
A great intro dataset for data exploration & visualization
palmerpenguins is an R package offering real-world ecological data from the Palmer Archipelago penguin species—Adélie, Chinstrap, and Gentoo. Designed as a more engaging alternative to the classical iris dataset, it provides size measurements, clutch information, and blood isotope data for teaching, visualization, and analytics practice. -
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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... -
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adv-r
Advanced R: a book
Source repository for Advanced R, the authoritative guide by Hadley Wickham, built with bookdown (R Markdown) and designed to deepen R users’ understanding of language internals, functional programming, object systems, and metaprogramming. -
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RNAseq Tutorial
Informatics for RNA-seq: A web resource for analysis on the cloud
rnaseq_tutorial is a tutorial and educational resource created by the Griffith Lab that guides users through the steps of RNA-seq data analysis. It includes working pipelines for alignment, differential expression, alternative splicing, visualization, and interpretation. It is designed to run in the cloud or local environments, providing introductory material on file formats, reference genomes / annotation, QC, mapping, quantifying expression, visualizing results, etc. The version in that... -
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Mastering Shiny
Mastering Shiny: a book
Mastering Shiny is a book (and its accompanying source repository) by Hadley Wickham that teaches people how to build interactive web applications using Shiny in R. It starts from basics (your first app, UI components, reactivity) and progresses to more advanced topics (dynamic UIs, modules, testing, security, performance). It is intended to help data scientists, analysts, or R users who may not have deep experience in web technologies become expert Shiny developers. The source code is open,... -
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Data Science Specialization
Course materials for the Data Science Specialization on Coursera
The Data Science Specialization Courses repository is a collection of materials that support the Johns Hopkins University Data Science Specialization on Coursera. It contains the source code and resources used throughout the specialization’s courses, covering a broad range of data science concepts and techniques. The repository is designed as a shared space for code examples, datasets, and instructional materials, helping learners follow along with lectures and assignments. It spans... -
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ProgrammingAssignment2
Repository for Programming Assignment 2 for R Programming on Coursera
This repository contains the second programming assignment for an R course, focused on caching expensive computations by leveraging R’s scoping rules. The assignment walks you through creating a special matrix object that stores both a matrix and its cached inverse, avoiding repeated calls to costly operations. It builds on a worked example that caches the mean of a numeric vector, demonstrating how the operator preserves state across function calls. You then implement analogous logic for... -
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ExData Plotting1
Plotting Assignment 1 for Exploratory Data Analysis
This repository explores household energy usage over time using the “Individual household electric power consumption” dataset from the UC Irvine Machine Learning Repository. The dataset covers nearly four years of minute-level measurements, including power consumption, voltage, current intensity, and detailed sub-metering values for different household areas. For analysis, focus is placed on a two-day period in February 2007, highlighting short-term consumption trends. The data requires...
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