ICML’24 Highlights: Neural Operators and the Physics of Language ModelsMy recent journey to ICML’24 in Vienna was very inspiring [with bits of overwhelm!]. The conference was a melting pot of innovative ideas…Oct 19Oct 19
Logistic Regression — General OverviewIn the early twentieth century, logistic regression was used mainly in the social and biological sciences. It is used as a classifier, to…Jan 21, 2022Jan 21, 2022
Human-Level Performance and Bayesian Optimal ErrorOn a lot of machine learning tasks, the progress of the model (in terms of accuracy) is relatively rapid in the beginning. However, as it…Jun 18, 20211Jun 18, 20211
Neural NetworksBefore we dive into explaining the core concepts of neural networks, I want to take some time and appreciate the remarkable and complex…Feb 6, 2021Feb 6, 2021
Ensemble Learning MethodsI want to start this article with a question —How many jelly beans exactly do you think there are in this jar? Give a wild guess…Dec 21, 20202Dec 21, 20202
Reinforcement LearningIn the previous articles, I have explained the underlying distinction between supervised and unsupervised learning, which was the presence…Nov 27, 2020Nov 27, 2020
Classical Machine Learning — Unsupervised Learning EditionEver wondered how the unsupervised machine learning work? Here, I explain them, and how are they used throughout the industry.Nov 4, 20201Nov 4, 20201
Classical Machine Learning — Supervised Learning EditionMachine Learning (ML) initially started in the ’50s and ’60s as pattern recognition, which means that algorithms learned by “seeing” more…Oct 3, 2020Oct 3, 2020
Navigating Into the World of Machine LearningWith the rapid expansion of Machine Learning as a field of research, it’s not easy to keep up with everything that is being invented and…Aug 15, 2020Aug 15, 2020
Fundamental Components of Machine LearningIn the following weeks I will share with you some articles with the intent to explain some machine learning concepts. A straightforward…Jul 20, 2020Jul 20, 2020
