A data orchestrator for machine learning, analytics, and ETL.
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Creates, rewrites or summarizes written content with language models.
Darknet is an open source neural network framework written in C and CUDA. It is fast, easy to install, and supports CPU and GPU computation.
Very simple implementation of neural networks for dummies in python without using any libraries, with detailed comments.
Data Science at Home is a podcast about machine learning, artificial intelligence, and algorithms.
Data Skeptic is a podcast hosted by Kyle Polich, featuring interviews with experts on data science, machine learning, AI, and statistics.
Enjoy unlimited API calls with Serverless AI Workers/LLMs for just $25 per month. No rate or concurrency limits.
Machine Learning framework for rapid development of Machine Learning and Statistical applications.
Upload a photo of any room, kitchen, exterior, or garden and get a photorealistic AI redesign in seconds. No design experience needed.
A python library for accurate and scalable fuzzy matching, record deduplication and entity-resolution.
A fast Clojure Tensor & Deep Learning library.
Translate texts & full document files instantly. Accurate translations for individuals and Teams. Millions translate with DeepL every day.
Scalable deep learning for industry with parallel GPUs.
Org profile for DeepSeek on Hugging Face, the AI community building the future.
Cheaper V4 model, supports thinking and non-thinking modes.
Deep learning optimization library that makes distributed training easy, efficient, and effective.
An open source machine learning framework in Rust Δ.
Track real-time GPU and LLM pricing across all cloud and inference providers.
AI-generated summaries of provided legal docs.
Train and run a computer vision model with 5-10 lines of code.
Scalable deep learning training platform with integrated hyperparameter tuning support; includes Hyperband, PBT, and other search methods.
Authors: Cal.com core team,, Ted Spare.
Deep learning in Rust, with shape checked tensors and neural networks.
. Practical AI engineering and generative AI explained simply: RAG, agents, and LLM application patterns for builders.