Amazon recently announced the launch of AutoGluon, a open source library for developers building applications involving machine learning (ML) with image, text or tabular data sets.
With Amazon AutoGluon, developers can harness the power of deep learning for building applications by writing just a few lines of code.
We developed AutoGluon to truly democratize machine learning, and make the power of deep learning available to all developers.
– Jonas Mueller, AWS Applied Scientist
AutoGluon automates many of these decisions for developers so that they can produce a high-performance neural network model with as few as three lines of code, says Amazon. There’s no need for developers to manually experiment with the hundreds of individual choices that must be made while designing a deep learning model. Rather, they can simply specify when they would like to have their trained model ready. In response, AutoGluon leverages the available compute resources to find the strongest model within its allotted run-time.
“Due to the inherently opaque nature of deep learning, many of the choices made by deep learning experts are based on ad hoc intuition, rather than a rigorous scientific understanding of how individual choices affect desired outcomes,” says Mueller. “AutoGluon solves this problem as all choices are automatically tuned within default ranges that are known to perform well for the particular task and model.”
Getting started with AutoGluon
The AutoGluon website features numerous tutorials for developers to leverage deep learning for tabular, text, & image data (covering both basic tasks like classification/regression as well as more advanced tasks like object detection). For more experienced developers, the AutoGluon Site features customization instructions on how to use AutoGluon APIs for automatically improving predictive performance in customized applications.
via: Amazon
