Matrix API library for the frontend.
A Node.js wrapper for Google Maps Distance Matrix API
A Node.js wrapper for Distance Matrix API offered by DistanceMatrixAPI.com
Google's distance matrix API
Javascript Matrix and Vector library for High Performance WebGL apps
Node.js wrapper for Goople Distance Matrix API.
Isochrone generator built atop the Mapbox Matrix API, with CONREC polygonization.
Matrix Client-Server SDK for Javascript
A simple react-native wrapper for Google's Distance Matrix API
Visualize relationships or network flow with an aesthetically-pleasing circular layout.
Welcome to the [Node.js] binding for the Rust [`matrix-sdk-crypto`] library! This binding is part of the [`matrix-rust-sdk`] project, which is a library implementation of a [Matrix] client-server.
A node distance matrix package that consumes Google Distance Matrix API to get distances between locations
Node.js API (Node-API)
Search and Rewrite code at large scale using precise AST pattern
Matrix manipulation and computation library
Matrix Widget API SDK
WebAssembly bindings of the matrix-sdk-crypto encryption library
Canvas for Node.js with skia backend
Creates and returns endpoint for Google Distance Matrix API.
Bing Distance Matrix - A NodeJS package for accessing the official Bing Distance Matrix API
A common util collection for antv projects
Chart.js module for creating matrix charts
2d transformation matrix functions written in ES6 syntax. Tree shaking ready!
https://docs.rs/lzma-rs binding to Node.js via https://napi.rs
# Endeavor The squash matrix API enables clubs, players, and regions to own their information, with results being updated weekly. The API information sits ontop of squash matrix australia website [https://squashmatrix.com](https://squashmatrix.com) # API Aside from the documentation provided below, there is also a `{json:api}` available and can be accessed in the same manner, with the addition of the accept header `{accept: application/vnd.api+json}`. More information about json api can be viewed on their website at [http://jsonapi.org/](http://jsonapi.org/) # Squash Matrix Scrapper There is a ruby SDK for retrieving information from [https://squashmatrix.com](https://squashmatrix.com) which can be found at https://rubygems.org/gems/squash_matrix # SDK's Please stay posted! Client sdk's for the following will be provided shortly: - Javascript - Java - Ruby # Blog Find relevent and interesting media on [wilkosz.com.au](http://wilkosz.com.au) # Contact Join this endeavor and be appart of the community [https://www.facebook.com/squashmatrixapi](https://www.facebook.com/squashmatrixapi) <hr />
Wrapper around the Google Maps Distance Matrix API.
Ruby client for The Google Distance Matrix API
Ruby implementation of the Matrix API
Simple Ruby wrapper for the Google Distance Matrix API.
Open Matrix Ruby API
Immutable persistent matrix using Hamster that aims to copy as much of the API from Ruby's native Matrix class as possible
Google Maps API Client, including the Routes API, Directions API, Distance Matrix API, Geocoding API and Places API. google_maps_service_ruby is a fork of google_maps_service, which is a fork of google-maps-services-python.
GRYDRA v2.0 is a complete, modular Ruby library for building, training, and deploying neural networks. NEW in v2.0: - Complete modular architecture with 29 organized files - Keyword arguments API for better readability - Full implementations (no more "simplified" versions) - 8 loss functions (MSE, MAE, Huber, Cross-Entropy, Hinge, Log-Cosh, Quantile) - 5 optimizers (Adam, SGD, RMSprop, AdaGrad, AdamW) - 6 training callbacks (EarlyStopping, LearningRateScheduler, ReduceLROnPlateau, ModelCheckpoint, CSVLogger, ProgressBar) - Complete LSTM implementation with backpropagation - Complete 2D Convolutional layer with padding and stride - Real PCA with eigenvalue decomposition using Power Iteration - Multiple activation functions (Tanh, ReLU, Leaky ReLU, Sigmoid, Swish, GELU, Softmax) - Regularization (Dropout, L1, L2) - Weight initialization (Xavier, He) - Data normalization (Z-Score, Min-Max) - Comprehensive metrics (MSE, MAE, Accuracy, Precision, Recall, F1, Confusion Matrix, AUC-ROC) - Advanced training (mini-batch, early stopping, learning rate decay, validation split) - Cross-validation and hyperparameter search - Text processing (vocabulary, binary vectorization, TF-IDF) - Model persistence (save/load with Marshal) - Network visualization and gradient analysis - Simplified EasyNetwork interface - 100% backward compatibility with v1.x Perfect for machine learning projects, research, and education in Ruby.
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