In case you missed it, here is Chris Mattmann and Dr. Scott Penberthy’s live Twitch coding stream recap. For more, check out the book: Machine Learning with TensorFlow, Second Edition. For more live coding streams, subscribe to Manning’s Twitch channel… Continue Reading →
From Deep Learning for Natural Language Processing by Stephan Raaijmakers
This article covers multitask learning for NLP.
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.
From Getting Started with Natural Language Processing by Ekaterina Kochmar
This article shows you how to extract the meaningful bits of information from raw text and how to identify their roles. Once you have roles identified, you can move on to syntactic parsing.
In this video, Hobson shows you how to move words from inflammatory to less inflammatory context with the help of word vectors (Word2vec).
In this video, Dr. Leonard Apelstin demonstrates xClustering Large Text Datasets in Python.
From Getting Started with Natural Language Processing by Ekaterina Kochmar
This article shows you how to extract the meaningful bits of information from raw text and how to identify their roles. Let’s first look into why identifying roles is important.
From Transfer Learning for Natural Language Processing by Paul Azunre
This article delves into using shallow transfer learning to improve your NLP models.
From Transfer Learning for Natural Language Processing by Paul Azunre
This article discusses getting started with baselines and generalized linear models.
Exploring Natural Language Processing is a free eBook with chapters selected by Hobson Lane.