The Best A gallery of interesting IPython notebooks Alternatives in 2026

mlxtend adds helper modules for Python data analysis and machine learning libraries.

AstroML provides Python tools for machine learning and data mining in astronomy.

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

emcee provides a Python toolkit for affine-invariant Markov chain Monte Carlo sampling.

For Python data preparation, DataPrep offers an open-source low-code library to collect, clean, and visualize data.

statsmodels provides statistical modeling and econometrics tools in Python.

Jupyter Notebook combines live code, equations, explanatory text, visualizations, and interactive computing in a web platform.

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

Segment Chinese text in PHP applications with jieba-php, a library for Chinese word tokenization.

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

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

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

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

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.

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

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.

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.