Standard iterator utilities.
The iterable toolbox
Fun with Iterables
The iterable toolbox
opensource free pure JavaScript cryptographic library supports RSA/RSAPSS/ECDSA/DSA signing/validation, ASN.1, PKCS#1/5/8 private/public key, X.509 certificate, CRL, OCSP, CMS SignedData, TimeStamp and CAdES and JSON Web Signature(JWS)/Token(JWT)/Key(JWK)
Basic operations on iterables
Joi extension for dates
A streaming data transport format that aims to support built-in features such as Promises, Dates, RegExps, Maps, Sets and more.
Higher order iterator library for JavaScript/TypeScript.
Core types for paging async iterable iterators
Transforming XML to JSON using Node.js binding to native pugixml parser library
parseArgs tokens compatibility and more high-performance parser
No-dependencies, low-level, high-performance JIT code generation package for JavaScript
TypeScript definitions for multimap
Joi extension for dates
Callbag operator that applies a transformation on data passing through it
Return an iterator's length.
Applies a callback to each value outputted by an iterable.
This project provides a collection of helper functions for working with asyncronous iterators in TypeScript.
A functional typescript implementation of the PCG family random number generators
IDEA's utility functions
Rush plugin for initialize project in monorepo
No description provided.
A collection of utilities for iterations.
Terraform's HCL lacks quite many programming features like iterators, true variables, advanced string manipulation, functions etc. This Ruby tool provides an easy-to-use DSL to define Terraform compatible .json files which can then be used with Terraform side-by-side with HCL files.
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.
Contentful API wrapper library exposing an ActiveRecord-like interface