The Best jieba-php Alternatives in 2026

Segment Chinese text with jieba, a Python package for natural language processing.

Python developers can use Zipline’s event-driven library to backtest algorithmic trading strategies.

Tesseract provides an open-source OCR engine for extracting text from images, with its main repository hosted on GitHub.

Machine learning pipelines can use whylogs, an open-source library for logging data quality and model performance.

This Node.js library implements Latent Dirichlet Allocation topic modeling in JavaScript.

The fastai deep learning library includes documentation and setup guidance, including instructions for use with Google Colab.

The Geni project provides a Clojure dataframe library that runs on Apache Spark.

Prediction with gradient boosting regression tree models is implemented in leaves, a Go software library.

Automatic machine learning, hyperparameter tuning, and pipeline abstractions are provided by the Neuraxle software library.

crystal-fann provides Crystal language bindings for the FANN artificial neural network library.

The Pattern Recognition Toolbox provides MATLAB tools for pattern recognition and machine learning.

Netron displays neural network, deep learning, and machine learning models across formats such as ONNX, TensorFlow, and PyTorch.

Browse large JSONL, Parquet, and CSV datasets in VS Code with the Bread Dataset Viewer extension.

jSciPy provides Java scientific computing tools for signal processing, FFT, filtering, power spectral density, and DCT.

ONNX-Scala provides an API and backend for deep and classical machine learning in Scala.

Opyrator turns machine learning code into microservices with a web API and interactive interface.

torchaudio provides data manipulation and transformation tools for audio signal processing with PyTorch.

Weights & Biases supports model training, fine tuning, and management from experimentation through production.

The anneal project is a Go machine learning compiler with graph rewriting, autodiff, and a WebGPU backend.

Sparkling Water brings H2O machine learning functionality into an Apache Spark cluster.

For Go developers, GoLearn provides a collection of tools for machine learning.

Mars provides tensor-based tools for large-scale computation with NumPy, Pandas, and scikit-learn.

Class-imbalanced machine learning is supported by imbalanced-ensemble, a toolbox for ensemble methods and datasets.

spaCy provides Python natural language processing tools for entity recognition, tagging, parsing, and word vectors.