Looking for something like MLDB? Here are 24 alternatives, ranked by how closely they match it on purpose, features and platforms. Of these, 1 are free or have a free plan and 14 are open source.
MLDB provides an open source database designed for machine learning projects.
| # | Alternative | Pricing | Open source | Platforms |
|---|---|---|---|---|
| 1 | Vaex | — | Not stated | Web |
| 2 | Netron | — | Not stated | Web |
| 3 | Accord.NET | — | Not stated | Web |
| 4 | DLib | — | Not stated | Web |
| 5 | astroML | — | Not stated | Web |
| 6 | Netron | — | Yes | Linux, macOS, Windows |
| 7 | ml5 | — | Yes | — |
| 8 | anneal | — | Yes | — |
| 9 | Microsoft ML for Apache Spark | — | Yes | — |
| 10 | mlxtend | — | Not stated | — |
Vaex provides out-of-core DataFrames for Python to explore and visualize large tabular datasets, with support for machine learning workflows.
Visualizer for neural network, deep learning and machine learning models.
Accord.NET combines machine learning with audio and image processing libraries in a C# framework.
dlib provides C++ libraries for image processing, machine learning, and related algorithms.
AstroML provides Python tools for machine learning and data mining in astronomy.
Netron displays neural network, deep learning, and machine learning models across formats such as ONNX, TensorFlow, and PyTorch.
The ml5.js project brings friendly machine learning tools to web projects.
The anneal project is a Go machine learning compiler with graph rewriting, autodiff, and a WebGPU backend.
SynapseML provides distributed machine learning algorithms for Spark through its Python library.
mlxtend adds helper modules for Python data analysis and machine learning libraries.
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.
Automatic machine learning, hyperparameter tuning, and pipeline abstractions are provided by the Neuraxle software 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.
Sparkling Water brings H2O machine learning functionality into an Apache Spark cluster.
For Go developers, GoLearn provides a collection of tools for machine learning.
Class-imbalanced machine learning is supported by imbalanced-ensemble, a toolbox for ensemble methods and datasets.
The fastai deep learning library includes documentation and setup guidance, including instructions for use with Google Colab.
Mars provides tensor-based tools for large-scale computation with NumPy, Pandas, and scikit-learn.
Jupyter Notebook combines live code, equations, explanatory text, visualizations, and interactive computing in a web platform.
For parallel computing in Python, Dask extends familiar tools to handle larger workloads.
spaCy provides Python natural language processing tools for entity recognition, tagging, parsing, and word vectors.
Apache Storm is an open-source distributed system for processing unbounded streams of data in real time.
Alternatives are suggested from the purpose and features described in our listings. Different pages for the same product appear once. Read each description to check whether it fits your task. How we choose alternatives · Suggest an alternative
