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Machine Learning Pipelines for Kubeflow.
YumCut - free AI video generator to turn a prompt into ready vertical videos for TikTok, Reels and YouTube Shorts. Auto script, scenes, voiceover, subtitles and watermark. Built with Next.js. Local-first pipeline + templates, batch rendering and API hooks for creators and indie makers. Self-hosted, FFmpeg-ready, multi-language output. Low cost fast
A lightweight Python library for building execution pipelines with retry, parallel execution, cron scheduling, and async support.
A library that builds, optimizes, and evaluates ML pipelines using domain-specific functions.
AutoML framework for the design of composite pipelines.
Aims at simplifying the Data Science experience of deploying Kubeflow Pipelines workflows.
LLM App is a Python library that helps you build real-time AI-powered data pipelines with few lines of code.
Python module that helps you build complex pipelines of batch jobs.
500+ ML/AI interview Q&A with runnable code — covers ML fundamentals, deep learning, NLP, PyTorch, scikit-learn pipelines, and system design.
Generic mechanism for data scientists to build, run, and monitor ML tasks and pipelines.
Machine learning model serving framework with dynamic batching and pipelined stages, provides an easy-to-use Python interface.
A framework providing the right abstractions to ease research, development, and deployment of your ML pipelines.
Fujitsu Research's post-training quantization pipeline for LLMs (QEP, AutoBit, JointQ, rotation) with vLLM plugin (arXiv:2603.28845).
Visual pipeline editor and workflow orchestrator with an easy to use UI and based on Kubernetes.
Open Source framework for voice and multimodal conversational AI.
CLI tool that allows you to build data profiles and write assertion tests for easily evaluating and tracking your data's reliability over time.