A very important technique in unsupervised machine learning as well as dimensionality reduction is Principal Component Analysis (PCA). But PCA is difficult to understand without the fundamental mathematical underpinnings. The two instructional videos below (Part 1 and 2) demonstrate PCA at an introductory level to provide an appreciation for this powerful tool used in big data applications.
PART 1:
PART 2:
In this sponsored post, Russell Ruben, director of automotive and emerging segment market, Western Digital, believes that as vehicle innovation continues over the next few years, driven by advances in sensors, 5G, AI, machine and deep learning and big data analytics, so must storage. Storage technology needs to keep up with the rapid pace of development as it becomes increasingly critical to support more and more demanding applications with mixed usages than ever before.
Generative AI tools, particularly Large Language Models (LLMs) such as ChatGPT, offer immense potential for solving all kinds of business problems, from creating documents to generating code. They can also introduce security risks in two novel ways: leaking information and introducing code vulnerabilities. This article explores the ways these challenges often arise across organizations and […]
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