Tag: Robust

Reducing Dimensionality of Hyperspectral Data with Robust PCA and Autoencoders in R

Background Hyperspectral images are images that capture a large number of spectral bands across the electromagnetic spectrum, usually hundreds of bands. While this provides a wealth of information, it also presents several challenges. One of the primary disadvantages of hyperspectral images is th...

Building a Custom Robust Retrieval Augmented Generation Chatbot

In today’s emerging AI market landscape, chatbots are a much desired additional value for many businesses and sectors. Driven by tremendous funding and highly active open-source innovation and research, the bet on generative AI, chatbots particularly, is growing heavier as the technology becom...

What Should You Do When Your Spouse is More Robust Than You?

My husband, daughter, her teenagers, and I went hiking over the Labor Day weekend. The kids spotted a steep incline studded with roots, and they were off like a herd of antelope, bounding higher. The rest of us tried to keep up, but I was the drag to their forward propulsion. The tread on my tenn...

AI is the last thing you should do, but you should do it.

When AI is the last step, you have a more robust final process because, first, you have investigated and improved before you automated the process. The AI model will benefit from the pruning of features as your continuous improvement advances. AI implementation will suffer less from inconsistent inp...

Robust Statistics for Data Scientists Part 2: Resilient Measures of Relationships Between Variables

Grasping the interconnections among variables is essential for making data-driven decisions. When we accurately evaluate these links, we bolster the trustworthiness and legitimacy of our findings, crucial in both scholarly and practical contexts. Data scientists frequently turn to Pearson’s...