github.com
Train and run a computer vision model with 5-10 lines of code.
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github.com
Authors: Cal.com core team,, Ted Spare.
newsletter.diamant-ai.com
. Practical AI engineering and generative AI explained simply: RAG, agents, and LLM application patterns for builders.
dify.ai
Dify supports deploying, serving, monitoring, or operating AI and machine-learning systems.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
dlib.net
DLib has C++ and Python interfaces for face detection and training general object detectors.
github.com
Library of SAS Enterprise Miner process flow diagrams to help you learn by example about specific data mining topics.
docketai.net
DocketAI — built on Replit. Update this description to reflect the app.
freedomaingenerator.com
Free AI domain generator with availability check and price comparison.
blog.dominodatalab.com
Dominodatalab supports deploying, serving, monitoring, or operating AI and machine-learning systems.
dosu.dev
Shared knowledge makes agents faster and more reliable.
github.com
Many useful features that aren't part of the main nn package.
github.com
Python library for scalable Bayesian optimisation.
github.com
Reading Wikipedia to answer open-domain questions.
github.com
High performance library for time series distances (DTW) and time series clustering.
github.com
Design and Deploy Large Language Model Apps.
github.com
Python library for experiment metrics logging into simply formatted local files.
github.com
An evolutionary optimization library.
huggingface.co
Works with speech, voice, music or other audio using machine-learning models.
huggingface.co
Works with speech, voice, music or other audio using machine-learning models.
emgu.com
Cross platform wrapper of OpenCV which can be compiled in Mono to be run on Windows, Linus, Mac OS X, iOS, and Android.
github.com
A library that builds, optimizes, and evaluates ML pipelines using domain-specific functions.
lakera.ai
Uncover LLM evaluation's importance and explore methods for assessing its performance and impact across industries.
cs.princeton.edu
Talk by Princeton professor Arvind Narayanan.