abdllah2's Stars
openai/whisper
Robust Speech Recognition via Large-Scale Weak Supervision
OpenInterpreter/open-interpreter
A natural language interface for computers
jekyll/jekyll
:globe_with_meridians: Jekyll is a blog-aware static site generator in Ruby
mozilla/pdf.js
PDF Reader in JavaScript
Asabeneh/30-Days-Of-Python
30 days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than100 days, follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw
Leaflet/Leaflet
π JavaScript library for mobile-friendly interactive maps πΊπ¦
myshell-ai/OpenVoice
Instant voice cloning by MIT and MyShell.
utmapp/UTM
Virtual machines for iOS and macOS
tinygrad/tinygrad
You like pytorch? You like micrograd? You love tinygrad! β€οΈ
modularml/mojo
The Mojo Programming Language
haotian-liu/LLaVA
[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.
trekhleb/learn-python
π Playground and cheatsheet for learning Python. Collection of Python scripts that are split by topics and contain code examples with explanations.
tidyverse/ggplot2
An implementation of the Grammar of Graphics in R
rstudio/cheatsheets
Posit Cheat Sheets - Can also be found at https://posit.co/resources/cheatsheets/.
huangsam/ultimate-python
Ultimate Python study guide for newcomers and professionals alike. :snake: :snake: :snake:
ReactiveX/RxPY
ReactiveX for Python
hadley/r4ds
R for data science: a book
ourownstory/neural_prophet
NeuralProphet: A simple forecasting package
matplotlib/mplfinance
Financial Markets Data Visualization using Matplotlib
meta-llama/PurpleLlama
Set of tools to assess and improve LLM security.
shashankvemuri/Finance
150+ quantitative finance Python programs to help you gather, manipulate, and analyze stock market data
6pac/SlickGrid
A lightning fast JavaScript grid/spreadsheet
google/visualblocks
Visual Blocks for ML is a Google visual programming framework that lets you create ML pipelines in a no-code graph editor. You β and your users β can quickly prototype workflows by connecting drag-and-drop ML components, including models, user inputs, processors, and visualizations.
SciRuby/daru
Data Analysis in RUby
joshuaulrich/quantmod
Quantitative Financial Modelling Framework
theOGognf/finagg
A Python package for aggregating and normalizing historical data from popular and free financial APIs.
RamiKrispin/shinylive-r
A guide for deploying Shinylive R application into Github Pages
RamiKrispin/ai-dev-2024-ml-workshop
Materials for the AI Dev 2024 conference workshop "Deploy and Monitor ML Pipelines with Python, Open Source, and Free Applications"
linuxscout/qutrub
Qutrub: Arabic verb conjugator
r0x0r/awesome-python
A curated list of awesome Python frameworks, libraries, software and resources