a fast newline (or any delimiter) splitter stream - like require('split') but faster
TypeScript definitions for binary-split
split/binary-split but lines contain byte offset in the source stream and gives access to last line fragment
Adaptive tessellation curve system with segment-based composition and binary split caching
A Transform Stream that splits a stream into chunks based on a delimiter
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Fast, buffer-based stream splitter supporting both push and pull streams
Easy way to split a string on a given character unless it's quoted or escaped.
Split a string on the first occurance of a given separator
split a Text Stream into a Line Stream, using Stream 3
Transform a string between `camelCase`, `PascalCase`, `Capital Case`, `snake_case`, `kebab-case`, `CONSTANT_CASE` and others
split a Text Stream into a Line Stream
Split a LineString by another GeoJSON Feature.
Check if a file path is a binary file
List of binary file extensions
Split Cypress specs across parallel CI machines for speed
Split string by any separator excluding brackets, quotes and escaped characters
React split-pane component with hooks and TypeScript
Split JavaScript SDK common components
Use Datadog from your CI.
Simple module to split a single certificate authority chain file (aka: bundle, ca-bundle, ca-chain, etc.) into an array, as expected by the node.js tls api.
React component for Split.js
Helper function to build binary assignment operator visitors
React split-pane component
A premium interactive terminal disk usage visualizer
Jittered fractional indexing for collision avoidance
Command line utility that can split files into chunks, join them together. All is done in binary mode making it encoding independent.
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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