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!
In this video, Hobson shows you how to move words from inflammatory to less inflammatory context with the help of word vectors (Word2vec).