AI - mLeap
Simplifying machine learning model building and deployment across frameworks with mLeap.
- Name
- mLeap -https://github.com/combust/mleap
- Last Audited At
About mLeap
mLeap is a machine learning library that provides various tools for building and deploying machine learning models using different frameworks like Spark MLlib, Scala Breeze, XGBoost, and TensorFlow. The company develops pipelines to preprocess data, apply transformations, and encode labels using techniques such as one-hot encoding.
Using TensorFlow 2.7.0 as an example, mLeap offers a Vector Assembler for One Hot Encoder with the functionality encapsulated in the one_hot_encoder_tf module. The library provides configurations to work with different versions of Spark, Scala, Java, Python, XGBoost, and TensorFlow. These combinations are listed above.
mLeap's core mission is to simplify the process of building machine learning models using various frameworks and make it easier for data scientists and engineers to apply them to their datasets. With a focus on compatibility and interoperability, mLeap enables users to work with popular libraries while ensuring seamless integration between different components.