Awesome List Updates on Jan 14, 2025

10 awesome lists updated today.

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1. Awesome for Beginners

Elm

• Exosphere (label: Good First Issue)
  Exosphere is a user-friendly client interface for OpenStack-based cloud systems.

JavaScript

• Mattermost (⭐33k) (label: Good First Issue, Difficulty/1:Easy)
  Open source Slack-alternative in Golang and React
  Look for issues labelled 'Up For Grabs'

Go

• PureLB (label: n/a)
  Load-balancer orchestrator for Kubernetes that uses standard Linux networking and routing protocols.

Java

• XWiki (label: onboarding)
  XWiki is a free wiki software platform written in Java with a design emphasis on extensibility. Beginners should follow the onboarding wiki.

TypeScript

• Readest (⭐9.5k) (label: good first issue)
  A modern, feature-rich ebook reader designed for avid readers offering seamless cross-platform access, powerful tools, and an intuitive interface.

Rust

• Veloren (label: n/a)
  Veloren is a multiplayer voxel RPG written in Rust.

2. Awesome Ios

Charts

• Charts (⭐28k) - A powerful chart/graph framework, the iOS equivalent to MPAndroidChart (⭐38k).

• CoreCharts (⭐71) - CoreCharts is a simple powerful yet Charts library for apple products.

• core-plot (⭐2.8k) - A 2D plotting lib which is highly customizable and capable of drawing many types of plots.

• CSPieChart (⭐41) - iOS PieChart Opensource. This is very easy to use and customizable.

• DDSpiderChart (⭐97) - Easy to use and customizable Spider (Radar) Chart library for iOS written in Swift.

• Dr-Charts (⭐94) - Dr-Charts is a highly customisable, easy to use and interactive chart/graph framework in Objective-C.

• EChart (⭐645) - iOS/iPhone/iPad Chart, Graph. Event handling and animation supported.

• EatFit (⭐650) - Eat fit is a component for attractive data representation inspired by Google Fit.

• FSLineChart (⭐847) - A line chart library for iOS.

• Graphs (⭐974) - Light weight charts view generator for iOS.

• JBChartView (⭐3.7k) - iOS-based charting library for both line and bar graphs.

• MagicPie (⭐530) - Awesome layer-based pie chart. Fantastically fast and fully customizable. Amazing animations available with MagicPie.

• PNChart (⭐9.7k) - A simple and beautiful chart lib used in Piner and CoinsMan for iOS.

• Scrollable-GraphView (⭐5.3k) - An adaptive scrollable graph view for iOS to visualise simple discrete datasets. Written in Swift.

• TEAChart (⭐1.2k) - Simple and intuitive iOS chart library. Contribution graph, clock chart, and bar chart.

• TKRadarChart (⭐211) - A customizable radar chart in Swift.

• TWRCharts (⭐360) - An iOS wrapper for ChartJS. Easily build animated charts by leveraging the power of native Obj-C code.

• XJYChart (⭐872) - A Beautiful chart for iOS. Support animation, click, slide, area highlight.

3. Awesome Webxr

Audio

• Fathom VR - A WebXR version of the music discovery app Fathom, which lets you search for and explore clouds of related artists with spatialized audio.

4. Awesome Angular

Cookies / Google Developer Experts

• ngx-cookie-ssr (⭐3) - A straightforward cookie service for Angular 19 applications, inspired by ngx-cookie-service.

5. Awesome Transit

GTFS Realtime (and Other Real-time API) Archival Tools / Rust

• gtfsdb_realtime (⭐12) - Real-time GTFS database loader and ORM library

6. Awesome Zig

Misc libraries

• pblischak/zprob (⭐10) - Module for Random Number Distributions.

7. Awesome Datascience

Other Awesome Lists / Book Deals (Affiliated)

• AI in Data Science: Uses, Roles, and Tools

• Top 13 Data Science Programming Languages

8. Awesome Go

Other Software / Libraries for creating HTTP middlewares

• goblin - Cloud builder for CLI's written in go lang

9. Awesome Neovim

Bars and Lines / Diagnostics

• mawkler/hml.nvim (⭐25) - Adds H/M/L indicators to your line numbers.

10. Awesome Agi Cocosci

Bayesian Modeling / Bayesian Induction

• Word learning as Bayesian inference - Psychological Review, 2007. [All Versions]. [Preprint]. The authors present a Bayesian framework for understanding how adults and children learn the meanings of words. The theory explains how learners can generalize meaningfully from just one or a few positive examples of a novel word's referents, by making rational inductive inferences that integrate prior knowledge about plausible word meanings with the statistical structure of the observed examples. The theory addresses shortcomings of the two best known approaches to modeling word learning, based on deductive hypothesis elimination and associative learning. Three experiments with adults and children test the Bayesian account's predictions in the context of learning words for object categories at multiple levels of a taxonomic hierarchy. Results provide strong support for the Bayesian account over competing accounts, in terms of both quantitative model fits and the ability to explain important qualitative phenomena. Several extensions of the basic theory are discussed, illustrating the broader potential for Bayesian models of word learning.

• How to Grow a Mind: Statistics, Structure, and Abstraction - Science, 2011. [All Versions]. [Preprint]. This review describes recent approaches to reverse-engineering human learning and cognitive development and, in parallel, engineering more humanlike machine learning systems. Computational models that perform probabilistic inference over hierarchies of flexibly structured representations can address some of the deepest questions about the nature and origins of human thought: How does abstract knowledge guide learning and reasoning from sparse data? What forms does our knowledge take, across different domains and tasks? And how is that abstract knowledge itself acquired?

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