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 want ...

Semi-supervised and unsupervised learning methods seek to extract structure and predictive power from data when labelled examples are scarce or absent. Unsupervised learning targets patterns and ...

The training process for artificial intelligence (AI) algorithms is designed to be largely automated innately. There are often thousands, millions or even billions of data points and the algorithms ...

This is part Three of my series based on Lomit Patel’s “Lean AI” (O’Reilly, ISBN:978-1-492-05931-8). The first two described supervised and unsupervised learning and gave examples of business ...

Use modern machine learning tools and python libraries. Explain how to deal with linearly-inseparable data. Compare logistic regression’s strengths and weaknesses. Explain what decision tree is & how ...

Self-supervised models generate implicit labels from unstructured data rather than relying on labeled datasets for supervisory signals. Self-supervised learning (SSL), a transformative subset of ...

Machine learning (ML) is a method of data analysis that automates analytical model building. It’s a branch of artificial intelligence (AI) based on the idea that systems can learn from data, identify ...