Explainable AI (XAI) refers to the capability of an artificial intelligence system to provide transparent and interpretable insights into its decision-making processes, allowing humans to understand and trust the reasoning behind the model's predictions or actions. It involves designing AI algorithms and models in a way that enables users to comprehend the factors influencing outcomes and ensures accountability and ethical use of AI technologies.
Click Here to open this notebook in colab:
- Free Course with certificate: https://aiplanet.com/learn/explainable-ai/introduction-to-explainable-ai
- Tutorial: https://www.datacamp.com/tutorial/explainable-ai-understanding-and-trusting-machine-learning-models
- Blog: https://towardsdatascience.com/explainable-ai-understanding-the-decisions-of-a-convolutional-neural-network-part-1-1a9cf26364fd