The power of machine learning comes at a price. Once you have the skills, the toolkit, the hardware, and the data, there is still the complexity involved in creating and fine-tuning a machine learning model.But if the whole point of machine learning is to automate tasks that previously required a human being at the helm, wouldn’t it be possible to use machine learning to take some of the drudgework out of machine learning itself?[ Review: TensorFlow, Spark MLlib, Scikit-learn, MXNet, Microsoft Cognitive Toolkit, and Caffe machine learning and deep learning frameworks. | Roundup: 13 frameworks for mastering machine learning. | Cut to the key news and issues in cutting-edge enterprise technology with the InfoWorld Daily newsletter. ]
Short answer: a qualified yes.

A collection of techniques, under the general banner of “automated machine learning,” or AML, can reduce the work needed to prepare a model and refine it incrementally to improve its accuracy.To read this article in full or to leave a comment, please click here

Leave a Reply