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Easy way to turn any app into searchable data for LLMs.
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Published directory entries matching your search.
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Ambrosia helps you clean up your LLM datasets using other LLMs.
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Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler.
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Platform for Production Data Science.
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Scripts to generate a dataset with static frames from the Arcade Learning Environment.
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AI Native database for embedding vectors.
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) - A fast web client boilerplate written in C# / Blazor, that uses an in-browser SQLite database.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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bulk-downloader-for-reddit helps export or download comments, posts, media, or discussion data from online platforms.
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An easy-to-use feature store. Optimized for time-series data.
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Basic functions for clustering data: k-means, dp-means, etc.
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A comparative framework for multimodal recommender systems with a focus on models leveraging auxiliary data.
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Very simple implementation of neural networks for dummies in python without using any libraries, with detailed comments.
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LinkedIn's generalized metadata search & discovery tool.
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Database client with AI-powered query assistance to generate context based queries.
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) - reference implementation of a DVM (Data Vending Machine) backend
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) - A lightweight, post-only Nostr client that compresses media on your device for fast, data-efficient uploads
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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A Virtual Feature Store. Turn your existing data infrastructure into a feature store.
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grab-site is an open source web scraping or crawling project for collecting website data.
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Pandas AI is a Python library that integrates LLMs capabilities into Pandas, making dataframes conversational.
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Open source video stabilization tool using gyro data for smooth action-camera footage.
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A scalable general purpose micro-framework for defining dataflows.
IPython notebooks from Data School's video tutorials on scikit-learn.