Machine learning pipelines can use whylogs, an open-source library for logging data quality and model performance.
Microsoft ML for Apache Spark vs Neuraxle
How do Microsoft ML for Apache Spark and Neuraxle compare? Here are the facts side by side: pricing, platforms, open-source status and what each one is for.
| Directory detail | Microsoft ML for Apache Spark | Neuraxle |
|---|---|---|
| What it is | SynapseML provides distributed machine learning algorithms for Spark through its Python library. | Automatic machine learning, hyperparameter tuning, and pipeline abstractions are provided by the Neuraxle software library. |
| Website | ||
| Type | Open-source project | Open-source project |
| Topic | ||
| Pricing | Not confirmed | Not confirmed |
| Platforms | Not recorded | Not recorded |
| Open source | Yes | Yes |
| Language | English | English |
| Alternatives |
Other options to consider
Sites similar to both Microsoft ML for Apache Spark and Neuraxle.
Class-imbalanced machine learning is supported by imbalanced-ensemble, a toolbox for ensemble methods and datasets.
Vaex provides out-of-core DataFrames for Python to explore and visualize large tabular datasets, with support for machine learning workflows.
Sparkling Water brings H2O machine learning functionality into an Apache Spark cluster.
Weights & Biases supports model training, fine tuning, and management from experimentation through production.
The Pattern Recognition Toolbox provides MATLAB tools for pattern recognition and machine learning.







