Machine Learning

What is Causal Machine Learning and Why Should You Care?

From Causal Machine Learning by Robert Ness

Enhance machine learning with causal reasoning to get more robust and explainable outcomes. Power causal inference with machine learning to create next gen AI..There has never been a better time to get into building causal AI.

Read on for more.

From Machine Learning to Automated Machine Learning

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

Learn How to Model Language as Tensors

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 →

How to Build a Serverless “Cat Detector” System Interactively

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

Before You Model: planning and scoping

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.

Fine-Tuning a Pre-Trained ResNet-50

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.

Managing Data Sources in Machine Learning

From Graph-Powered Machine Learning by Alessandro Negro

This article discusses managing data in graph-powered machine learning projects.

Creating a Bipartite Graph for a User-Item Dataset

By Graph-Powered Machine Learning Alessandro Negro

This article discusses creating a bigraph for a user-item dataset.

Setting Limits on Experimentation

This article talks about the need to carefully plan a machine learning project—before you start it!

Deep Transfer Learning for NLP with Transformers

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.

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