Since I switched to the field of machine learning, I have been interested in its theoretical foundations—doing a lot of pure mathematics in before my Ph.D. (and a tiny bit during the Ph.D. as well) left its mark apparently. I noticed two things relatively... (more…)

AI is building technology that behaves like a human, whereas Machine learning is a subset of artificial intelligence that uses algorithms to learn from data sets.

Research papers with annotations, illustrations and explanations - Machine-Learning-Tokyo/papers-with-annotations... (more…)

Predicting the power or energy required to run an AI/ML algorithm is a complex task that requires accurate power models, none of which exist today. (more…)

Audio pre-processing for Machine Learning: Getting things right For any machine learning experiment, careful handling of input data in terms of cleaning, encoding/decoding, featurizing are paramoun... (more…)