Скачать или смотреть How Does Explainable AI Monitor ML Models? - AI and Machine Learning Explained

How Does Explainable AI Monitor ML Models? In this informative video, we will discuss the role of Explainable Artificial Intelligence (XAI) in monitoring machine learning models. We will cover how XAI enhances the understanding of model decisions, providing clarity and transparency throughout the model lifecycle. You'll learn about the importance of interpretability in tracking model performance, including traditional performance metrics and the additional insights provided by XAI techniques.

We will explore various methods, such as SHapley Additive exPlanations, that help teams assess the influence of different features on model predictions. This understanding is vital for identifying biases and performance issues, especially in complex models like large language models and computer vision systems.

Additionally, we will highlight the significance of human feedback and custom evaluation metrics in ensuring that AI models align with human values. Our discussion will also touch on the importance of continuous monitoring to detect issues like data drift and concept drift, which can affect model reliability over time.

Join us for this engaging discussion to learn how explainable AI contributes to building robust, fair, and transparent artificial intelligence systems. Don't forget to subscribe to our channel for more informative content on AI and machine learning!

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About Us: Welcome to AI and Machine Learning Explained, where we simplify the fascinating world of artificial intelligence and machine learning. Our channel covers a range of topics, including Artificial Intelligence Basics, Machine Learning Algorithms, Deep Learning Techniques, and Natural Language Processing. We also discuss Supervised vs. Unsupervised Learning, Neural Networks Explained, and the impact of AI in Business and Everyday Life.