Hello Reader:

This week we feature articles from Moez Ali, and Dan Robinson.

Additional reading comes from Ingrid Lunden, Michael Eisenstein, and Denise-Marie Ordway.

News comes from Netlify, Intrep-ID, Sitecore, Kentico, and Elastic.

Reminder: If you’ve missed any recent issues you can see them here.

Opinion / Analysis

Is LDA topic modeling dead?

If you’re a topic modeling geek you’ll want to check out Dan Robinson’s deep dive on how BERTopic addresses a couple of the important limitations of LDA. (14 min)


Natural language processing (NLP) Python libraries in 2022

Python has a growing ecosystem of open-source NLP libraries. This article lists down some of the really useful NLP libraries in Python in no particular order.

Moez Ali suggests the current top Python libraries are: Hugging Face Transformers, NLTK, spaCy, Gensim, and Flair. (4 min)


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More Reading…

Content technology news

Introduction to Intrepids

A way to manage personal data. Individuals can manage and reuse their data efficiently while enhancing data privacy, and increasing data control.

Sitecore releases Experience Manager Cloud (XM Cloud)

They have transitioned the core CMS solution including personalization and the content authoring experience, to a modern cloud architecture.

Netlify announces investments for the Jamstack Innovation Fund

To support early-stage companies that are driving forward the modern web by arming developer teams with Jamstack-based tooling and practices.

Kentico to focus on CMS & DXP

Raised an investment of $40 million from Expedition Growth Capital and became a standalone enterprise. Kontent.ai is now a separate company.

Elastic enhances cross-cluster search and replication

Enables users to search across multiple clusters and visualize data in one view, and replicate data between clusters regardless of physical location.

All content technology news

The Gilbane Advisor is curated by Frank Gilbane for content technology, computing, and digital experience professionals. The focus is on strategic technologies. We publish recommended articles and content technology news weekly. We do not sell or share personal data.

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