From Automated Machine Learning in Action by Qingquan Song, Haifeng Jin, and Xia Hu
This article covers
• Defining and introducing the fundamental concepts of machine learning
• Describing the motivation for and high-level concepts of automated machine learning
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 →
In case you missed it, here is Peter Elger and Eoin Chanaghy’s live Twitch coding stream recap. For more, check out the book: AI as a Service. For more live coding streams, subscribe to Manning’s Twitch channel here: https://www.twitch.tv/manningpublications
From Machine Learning Engineering in Action by Ben Wilson
Before we get into how successful planning phases for ML projects are undertaken, let’s go through a simulation of the genesis of a typical project at a company that doesn’t have an established or proven process for initiating ML work.
From Transfer Learning in Action Dipanjan Sarkar and Raghav Bali
This article delves into tuning up a pre-trained ResNet-50 with one-cycle learning rate.
From Graph-Powered Machine Learning by Alessandro Negro
This article discusses managing data in graph-powered machine learning projects.
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).