A cloud-native vector database, storage for next generation AI applications
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Updated
Nov 27, 2024 - Go
A cloud-native vector database, storage for next generation AI applications
RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.
cuVS - a library for vector search and clustering on the GPU
EEG inverse solution with artificial neural networks. This package works with MNE-Python data structures for easy integration into your MNE-based M/EEG code
Shotit is a screenshot-to-video search engine tailored for TV & Film, blazing-fast and compute-efficient.
Deep learning (also known as deep structured learning or hierarchical learning) is part of a broader family of machine learning methods based on artificial neural networks. Learning can be supervised, semi-supervised or unsupervised. Deep learning architectures such as deep neural networks, deep belief networks, recurrent neural networks and con…
AI@UCF's custom-made course, organized by semesters
Simple gRPC server for vector searching implemented by Python and Faiss
Naive implementations of some ANNS (Approximate Nearest Neighbor Search) algorithms without any optimization and generalization.
The ultimate brain of Shotit, in charge of task coordination.
Four core workers of shotit: watcher, hasher, loader and searcher.
Media broker for serving video preview for shotit
Sort the search results of Shotit to increase the correctness of Top1 result by using Keras and Faiss.
In this Repository, we intend to implement the DQN and also the DDQN algorithm in case of training an agent to solve the Lunar-Lander problem. there are lots of exciting results after training which have been attached.
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