Piercing the Black Box: ELI5
ELI5 (Explain Like I'm 5) is a Python library designed to provide clear, easy-to-understand explanations of machine learning models and their predictions. It offers various tools for interpreting and visualizing the inner workings of models, making it easier for non-technical stakeholders to grasp the decisions made by complex algorithms.
Piercing the Black Box: LIME
Local Interpretable Model-Agnostic Explanations (LIME) is a Python library designed to provide clear, easy-to-understand explanations of machine learning models and their predictions. It offers various tools for interpreting and visualizing the inner workings of models, making it easier for non-technical stakeholders to grasp the decisions made by complex algorithms.
SocialView by Delphi Intelligence
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Piercing the Black Box: SHAP
One common criticism of machine learning and AI is that the reasoning behind its output can be obscure. This is what's known as the “black box” of AI. However, despite this common misconception, AI & machine learning models can be understood through a variety of techniques that examine the importance of the features that go into a model.
Yes, we KAN!
For years, a type of artificial neural network called Multi-Layer Perceptrons (MLPs) has been the backbone of many machine learning applications, from basic classification tasks to cutting-edge models like transformers and large language models. However, in April 2024, Liu et al. introduced a revolutionary new approach called Kolmogorov-Arnold Networks (KANs), drawing inspiration from a mathematical concept known as the Kolmogorov-Arnold representation theorem.
