Cross Entropy Loss and Uses in Machine Learning
Why it matters: Cross Entropy Loss is a widely used loss function in machine learning, particularly in classification models.
Rachel StClair
Rachel St.Clair, PhD., is a scientist, entrepreneur and author. She is a co-founder of Simuli Inc. Her passion and goal is to help build beneficial AGI. Rachel continues to be an active scientific member of the AI community by publishing and collaborating in the field. When Rachel’s not working on AI, she likes to go whale watching, write and read science fiction novels, and develops cartoons and video games.
Introduction to Vector Norms: L0, L1, L2, L-Infinity
Why it matters: Vector norms: L0 L1 L2 L-Infinity are fundamental concepts in mathematics and machine learning that allow us to measure magnitude of vectors.
What is Transfer Learning And How Is It Used In Machine Learning?
Why it matters: Transfer learning is a machine learning technique that allows for the reuse of knowledge from solving one problem to a related problem.
What is UNet? How Does it Relate to Deep Learning?
Why it matters: What is UNet? UNet is a powerful deep learning architecture that is widely used in image segmentation tasks.
PCA-Whitening vs ZCA Whitening: What is the Difference?
Why it matters: PCA-Whitening vs ZCA Whitening: What is the Difference? These are two powerful techniques for preprocessing and dimensionality reduction in ML
What Are Siamese Networks? An Introduction
Why it matters: What Are Siamese Networks? These have a unique structure, where two or more identical network inputs are processed and outputs compared.