By Graph-Powered Machine Learning Alessandro Negro
This article discusses creating a bigraph for a user-item dataset.
This article talks about the need to carefully plan a machine learning project—before you start it!
From Transfer Learning for Natural Language Processing by Paul Azunre
In this article, we cover some representative deep transfer learning modeling architectures for NLP that rely on a recently popularized neural architecture – the transformer – for key functions.
In this video, Hobson shows you how to move words from inflammatory to less inflammatory context with the help of word vectors (Word2vec).
Hefin I. Rhys teaches you how to train, tune, and cross-validate a Support Vector Machine model using RStudio and the awesome mlr machine learning package.
Learn the most important tools in the repertoire of a data scientist and machine learning practitioner – Principal Component Analysis (PCA), Singular Value Decomposition (SVD), and Latent Semantic Analysis (LSA) – with the help of Krishnendu Chaudhury.
Deep dive with Carl Osipov into understanding automatic differentiation used by PyTorch autograd for deep learning
Exploring Natural Language Processing is a free eBook with chapters selected by Hobson Lane.
Exploring Machine Learning Basic is a free eBook with chapters selected by Luis G. Serrano.
Why speed read this, you ask? Learn how AI can plow through an inbox at superhuman speeds. Let an AI summarize and help you focus. That’s what I need. [ed. This is my first joint blog post with Chris Mattmann,… Continue Reading →