Andrew Ng, a major figure in machine learning and AI, did not directly invent [[Latent Dirichlet Allocation]] ([[LDA]]). Here's how to break it down: - **LDA Inventors:** LDA was primarily developed by David Blei, Andrew Ng, and Michael Jordan. Their 2003 paper is considered the foundational work on LDA. - **Andrew Ng's Role:** Andrew Ng contributed significantly to the development and popularization of LDA. He co-authored the key paper and has lectured extensively on the topic. - **Ng's Other AI Work:** Andrew Ng is famous for his broad contributions to AI, including: - **Co-founding Coursera:** The online learning platform - **Leading Google Brain:** Deep learning research group at Google. - **Founding Deeplearning.ai:** To make AI education more accessible. **Latent Dirichlet Allocation (LDA)** Just to be thorough, here's a quick summary of LDA: - **Purpose:** LDA is a probabilistic topic modeling technique used in natural language processing. It helps uncover hidden thematic patterns ("topics") within large collections of text documents. - **How it Works:** It treats documents as a mixture of topics, where each topic is a probability distribution over words. # References ```dataview Table title as Title, authors as Authors where contains(subject, "Andrew Ng") or contains(authors, "Andrew Ng") sort title, authors, modified, desc ```