mlxtend adds helper modules for Python data analysis and machine learning libraries.
DataPrep vs Microsoft ML for Apache Spark
How do DataPrep and Microsoft ML for Apache Spark compare? Here are the facts side by side: pricing, platforms, open-source status and what each one is for.
| Directory detail | DataPrep | Microsoft ML for Apache Spark |
|---|---|---|
| What it is | For Python data preparation, DataPrep offers an open-source low-code library to collect, clean, and visualize data. | SynapseML provides distributed machine learning algorithms for Spark through its Python 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 DataPrep and Microsoft ML for Apache Spark.
Machine learning pipelines can use whylogs, an open-source library for logging data quality and model performance.
The Geni project provides a Clojure dataframe library that runs on Apache Spark.
Class-imbalanced machine learning is supported by imbalanced-ensemble, a toolbox for ensemble methods and datasets.
jSciPy provides Java scientific computing tools for signal processing, FFT, filtering, power spectral density, and DCT.
DataComPy compares Pandas, Polars, Spark, and Snowpark dataframes, with output that includes comparison statistics.







