AutoMLPipeline
Development & TrainingWhat is AutoMLPipeline?
It is a package that makes it trivial to create complex ML pipeline structures using simple expressions. It leverages on the built-in macro programming features of Julia to symbolically process, manipulate pipeline expressions, and automatically discover optimal structures for machine learning prediction and classification.
AutoMLPipeline is a tool in the Development & Training category of a tech stack.
Key Features
Pipeline API that allows high-level description of processing workflowCommon API wrappers for ML libs including Scikitlearn, DecisionTree, etcSymbolic pipeline parsing for easy expression of complexed pipeline structuresEasily extensible architecture by overloading just two main interfaces: fit! and transform!Meta-ensembles that allow composition of ensembles of ensembles (recursively if needed) for robust prediction routinesCategorical and numerical feature selectors for specialized preprocessing routines based on types
AutoMLPipeline Pros & Cons
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AutoMLPipeline Alternatives & Comparisons
What are some alternatives to AutoMLPipeline?
TensorFlow
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
NumPy
Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.
Jupyter
The Jupyter Notebook is a web-based interactive computing platform. The notebook combines live code, equations, narrative text, visualizations, interactive dashboards and other media.
