An in-depth introduction to the field of machine learning, from linear models to deep learning and reinforcement learning, through hands-on Python projects. — Part of the MITx MicroMasters program in Statistics and Data Science.

Deep learning face recognition models are used by state-of-the-art surveillance systems to identify individuals passing through public areas (e.g., airports). Previous studies have demonstrated the use of adversarial machine learning (AML) attacks to succ…

The rapid recent progress in machine learning (ML) has raised a number of scientific questions that challenge the longstanding dogma of the field. One of the most important riddles is the good empirical generalization of overparameterized models. Overpara…

by David Berg, Ravi Kiran Chirravuri, Romain Cledat, Savin Goyal, Ferras Hamad, Ville Tuulos…

Research in machine learning (ML) has primarily argued that models trained on incomplete or biased datasets can lead to discriminatory outputs. In this commentary, we propose moving the research focus beyond bias-oriented framings by adopting a power-awar…

How the hyperparameters of our machine learning models are tuned at Canva…

The most important step for a successful ML project…

How the hyperparameters of our machine learning models are tuned at Canva…

TL;DR – I wrote annotation-mode, which is a emacs minor mode for annotating text documents for machine learning purposes. Recently at work I had to annotate some text documents for a piece of NLP work. The annotation involves marking regions of the text …