Stars
This is the first step of expressing my pure hate towards AI job screening stuff that companies use to "screen" our application without even a human looking into it, we dont take sticks to a sword …
An object oriented PHP driver for FFMpeg binary
A SnapHelper that snaps a RecyclerView to an edge.
SwiftSoup: Pure Swift HTML Parser, with best of DOM, CSS, and jquery (Supports Linux, iOS, Mac, tvOS, watchOS)
A tagging plugin for Rails applications that allows for custom tagging along dynamic contexts.
Awesome MCP Servers - A curated list of Model Context Protocol servers
An autocompletion daemon for the Go programming language
This repository contains opportunities for you to apply to more than 400 product base companies(NOT JUST FAANGM) & good start-ups.
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
Course Files for Complete Python 3 Bootcamp Course on Udemy
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 or handson-mlp instead.
A collection of notebooks/recipes showcasing some fun and effective ways of using Claude.
10 Weeks, 20 Lessons, Data Science for All!
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
Data Engineering Zoomcamp is a free 9-week course on building production-ready data pipelines. The next cohort starts in January 2026. Join the course here 👇🏼
🔊 Text-Prompted Generative Audio Model
This is a repo with links to everything you'd ever want to learn about data engineering
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
12 Weeks, 24 Lessons, AI for All!
Learn how to develop, deploy and iterate on production-grade ML applications.
Python Data Science Handbook: full text in Jupyter Notebooks
12 Lessons to Get Started Building AI Agents
Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs,…
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.