Supervised machine learning is a subset of machine learning that operates under a tightly defined set of rules. In this approach, algorithms learn from a preexisting labeled data set, also known ...

In recent articles I have looked at some of the terminology being used to describe high-level Artificial Intelligence concepts – specifically machine learning and deep learning. In this piece, I ...

The machine learning system must teach itself to classify the data, processing the unlabeled data to learn from its inherent structure. In the case of semi-supervised learning — a bridge between ...

Explain how to deal with linearly-inseparable data. Compare logistic regression’s strengths and weaknesses. Explain what decision tree is & how it splits nodes. This week, we will build our supervised ...

This is an example of how a peripheral measure identified with machine-learning strategies ... the farming (vs mining) paradigm is the incentive to the end-users who submit data to the ‘farm ...

Supervised learning of a neural network is done just like any other machine learning: You present the network with groups of training data, compare the network output with the desired output ...

Beyond regression models, you can use Excel for other machine learning algorithms. Learn Data Mining Through Excel provides a rich roster of supervised and unsupervised machine learning algorithms ...

Jared Dean's Big Data, Data Mining, and Machine Learning promises to help business leaders understand the potential and provide guidance for those faced with putting the techniques into practice.

This is rarely the last step since the owner of the raw data typically applies more sophisticated deep learning or supervised machine learning analyses to any potentially interesting patterns.

The MLDM´2018 conference is the fourteenth event in a series of Machine Learning and Data Mining meetings. The aim of MLDM is to bring together from all over the world researchers dealing with ...