130 skills found · Page 1 of 5
ashvardanian / NumKongSIMD-accelerated distances, dot products, matrix ops, geospatial & geometric kernels for 16 numeric types — from 6-bit floats to 64-bit complex — across x86, Arm, RISC-V, and WASM, with bindings for Python, Rust, C, C++, Swift, JS, and Go 📐
ibarrond / PyfhelPYthon For Homomorphic Encryption Libraries, perform encrypted computations such as sum, mult, scalar product or matrix multiplication in Python, with NumPy compatibility. Uses SEAL/PALISADE as backends, implemented using Cython.
QuantumKitHub / MPSKit.jlA Julia package dedicated to simulating quantum many-body systems using Matrix Product States (MPS)
piyushpathak03 / Recommendation SystemsRecommendation Systems This is a workshop on using Machine Learning and Deep Learning Techniques to build Recommendation Systesm Theory: ML & DL Formulation, Prediction vs. Ranking, Similiarity, Biased vs. Unbiased Paradigms: Content-based, Collaborative filtering, Knowledge-based, Hybrid and Ensembles Data: Tabular, Images, Text (Sequences) Models: (Deep) Matrix Factorisation, Auto-Encoders, Wide & Deep, Rank-Learning, Sequence Modelling Methods: Explicit vs. implicit feedback, User-Item matrix, Embeddings, Convolution, Recurrent, Domain Signals: location, time, context, social, Process: Setup, Encode & Embed, Design, Train & Select, Serve & Scale, Measure, Test & Improve Tools: python-data-stack: numpy, pandas, scikit-learn, keras, spacy, implicit, lightfm Notes & Slides Basics: Deep Learning AI Conference 2019: WhiteBoard Notes | In-Class Notebooks Notebooks Movies - Movielens 01-Acquire 02-Augment 03-Refine 04-Transform 05-Evaluation 06-Model-Baseline 07-Feature-extractor 08-Model-Matrix-Factorization 09-Model-Matrix-Factorization-with-Bias 10-Model-MF-NNMF 11-Model-Deep-Matrix-Factorization 12-Model-Neural-Collaborative-Filtering 13-Model-Implicit-Matrix-Factorization 14-Features-Image 15-Features-NLP Ecommerce - YooChoose 01-Data-Preparation 02-Models News - Hackernews Product - Groceries Python Libraries Deep Recommender Libraries Tensorrec - Built on Tensorflow Spotlight - Built on PyTorch TFranking - Built on TensorFlow (Learning to Rank) Matrix Factorisation Based Libraries Implicit - Implicit Matrix Factorisation QMF - Implicit Matrix Factorisation Lightfm - For Hybrid Recommedations Surprise - Scikit-learn type api for traditional alogrithms Similarity Search Libraries Annoy - Approximate Nearest Neighbour NMSLib - kNN methods FAISS - Similarity search and clustering Learning Resources Reference Slides Deep Learning in RecSys by Balázs Hidasi Lessons from Industry RecSys by Xavier Amatriain Architecting Recommendation Systems by James Kirk Recommendation Systems Overview by Raimon and Basilico Benchmarks MovieLens Benchmarks for Traditional Setup Microsoft Tutorial on Recommendation System at KDD 2019 Algorithms & Approaches Collaborative Filtering for Implicit Feedback Datasets Bayesian Personalised Ranking for Implicit Data Logistic Matrix Factorisation Neural Network Matrix Factorisation Neural Collaborative Filtering Variational Autoencoders for Collaborative Filtering Evaluations Evaluating Recommendation Systems
jeremiah-k / Meshtastic Matrix RelayA relay between a Matrix room and a Meshtastic radio. This relay extends your Matrix.org-based communication with a LoRa-based Meshtastic radio mesh. This is not an official product of Matrix.org or Meshtastic.
jemisjoky / TorchMPSPyTorch toolbox for matrix product state models
joselado / DmrgpyDMRGPy is a Python library to compute quasi-one-dimensional spin chains and fermionic systems using matrix product states with DMRG as implemented in ITensor. Most of the computations can be performed both with DMRG and exact diagonalization for small systems, which allows one to benchmark the results.
ocramz / Sparse Linear AlgebraNumerical computation in native Haskell
amilsted / EvoMPSAn implementation of the time dependent variational principle for matrix product states
Pupariaa / Bk Light AppBypassAsync Python toolkit for driving the BK-Light ACT1026 32×32 AND ACT1025 16x64 RGB LED ("Action" Product) matrix over Bluetooth Low Energy — shared BLE session, image/text uploaders, counter demo, and auto-bootstrap scanner.
cmendl / PytenetPython implementation of quantum tensor network operations and simulations: matrix product states and operators, TDVP time evolution, support for quantum numbers, ...
dsuess / MpnumMatrix Product Representation library for Python
congzlwag / UnsupGenModbyMPScode for Unsupervised Generative Modeling using Matrix Product States
qiskit-community / LindbladmpoA matrix-product-operators solver for the dynamics of interacting qubits modeled by a Lindblad master equation, written in C++ and wrapped with an easy-to-use Python interface.
ITensor / ITensorInfiniteMPS.jlA package for working with infinite matrix product states (MPS) with ITensor.
TensorBFS / CMPOcontinuous-time matrix product operator for finite temperature quantum states
iVishalr / GEMMFast Matrix Multiplication Implementation in C programming language. This matrix multiplication algorithm is similar to what Numpy uses to compute dot products.
leburgel / UniformMpsTutorialTutorial on tangent space methods for uniform matrix product states.
orialb / TimeEvoMPS.jlTime evolution algorithms for matrix-product states based on ITensors.jl
dsuess / MptikzLuaTeX extension for graphical tensor notation
