Topic: anns Goto Github
Some thing interesting about anns
Some thing interesting about anns
anns,Fast and minimal header-only graph-based index for approximate nearest neighbor search (ANNS). https://blaisemuhirwa.github.io/flatnav-experimental
User: blaisemuhirwa
anns,HNSW tutorial
User: brtholomy
Home Page: https://www.bartholomy.ooo/posts/neural-topologies/
anns,GraphANNS 源链接
Organization: cdev-io
Home Page: https://github.com/whenever5225/GraphANNS
anns,Discover the main building blocks of neural networks and understand the three main neural network architectures. Explore the process of solving a regression data problem
Organization: develop-packt
anns,Naive implementations of some ANNS (Approximate Nearest Neighbor Search) algorithms without any optimization and generalization.
User: hhy3
anns,The goal is to make an Artificial Neural Network that can predict, based on geo-demographical and transactional information given above, if any individual customer will leave the bank or stay (customer churn). Also, rank all the customers of the bank, based on their probability of leaving.
User: ishan-kotian
Home Page: https://www.kaggle.com/lykin22/bank-customer-s-churn-classification-ann-dl
anns,Simple gRPC server for vector searching implemented by Python and Faiss
User: kanchishimono
anns,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
User: lukethehecker
anns,A cloud-native vector database, storage for next generation AI applications
Organization: milvus-io
Home Page: https://milvus.io
anns,Go SDK for Milvus.
Organization: milvus-io
anns,Java SDK for Milvus.
Organization: milvus-io
Home Page: https://milvus.io
anns,This repository contains materials and course projects during attending the Intelligent Systems Course, for more detailed information please have a look at my Final_Report files which have been separately uploaded for each of the projects and consist of all required information about the implementations, analyses, and anything else you may concern about that!
User: mohammad-heydariii
anns,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.
User: mohammad-heydariii
anns,Data Mining Class @ The Open University
User: netanelshoshan
anns,cuVS - a library for vector search and clustering on the GPU
Organization: rapidsai
Home Page: https://rapids.ai
anns,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.
Organization: rapidsai
Home Page: https://docs.rapids.ai/api/raft/stable/
anns,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 convolutional neural networks have been applied to fields including computer vision, speech recognition, natural language processing, audio recognition, social network filtering, machine translation, bioinformatics, drug design, medical image analysis, material inspection and board game programs, where they have produced results comparable to and in some cases superior to human experts.
User: reddyprasade
anns,The README profile of Shotit.
Organization: shotit
Home Page: https://shotit.github.io/
anns,Shotit is a screenshot-to-video search engine tailored for TV & Film, blazing-fast and compute-efficient.
Organization: shotit
Home Page: https://shotit.github.io
anns,The ultimate brain of Shotit, in charge of task coordination.
Organization: shotit
Home Page: https://shotit.github.io
anns,The frontend of shotit, with full documentation.
Organization: shotit
Home Page: https://shotit.github.io/
anns,Media broker for serving video preview for shotit
Organization: shotit
Home Page: https://shotit.github.io
anns,Provide meta information and utility for shotit, for example, image proxy, cast and poster etc.
Organization: shotit
Home Page: https://shotit.github.io/
anns,Sort the search results of Shotit to increase the correctness of Top1 result by using Keras and Faiss.
Organization: shotit
Home Page: https://shotit.github.io/
anns,Four core workers of shotit: watcher, hasher, loader and searcher.
Organization: shotit
Home Page: https://shotit.github.io/
anns,The front page to shotit.github.io
Organization: shotit
Home Page: https://shotit.github.io/
anns,perceptron, backprop, RBF, SOM, hopfield nets, autoencoders (no external ML libs)
User: tgll
anns,AI@UCF's custom-made course, organized by semesters
Organization: ucfai
Home Page: https://ucfai.org/groups/core
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