Hands-On Explainable Ai (xai) with Python

Hands-On Explainable Ai (xai) with Python - Opis

Effectively translating AI insights to business stakeholders requires careful planning, design, and visualization choices. Describing the problem, the model, and the relationships among variables and their findings are often subtle, surprising, and technically complex.Hands-On Explainable AI (XAI) with Python will see you work with specific hands-on machine learning Python projects that are strategically arranged to enhance your grasp on AI results analysis. You will be building models, interpreting results with visualizations, and integrating XAI reporting tools and different applications.You will build XAI solutions in Python, TensorFlow 2, Google Cloud’s XAI platform, Google Colaboratory, and other frameworks to open up the black box of machine learning models. The book will introduce you to several open-source XAI tools for Python that can be used throughout the machine learning project life cycle.You will learn how to explore machine learning model results, review key influencing variables and variable relationships, detect and handle bias and ethics issues, and integrate predictions using Python along with supporting the visualization of machine learning models into user explainable interfaces.By the end of this AI book, you will possess an in-depth understanding of the core concepts of XAI. Spis treści: 1. Explaining Artificial Intelligence with Python2. White Box XAI for AI Bias and Ethics3. Explaining Machine Learning with Facets4. Microsoft Azure Machine Learning Model Interpretability with SHAP5. Building an Explainable AI Solution from Scratch6. AI Fairness (...) więcej with Google's What-If Tool (WIT)7. A Python Client for Explainable AI Chatbots8. Local Interpretable Model-Agnostic Explanations (LIME)9. The Counterfactual Explanations Method10. Contrastive XAI11. Anchors XAI12. Cognitive XAI O autorze: Denis Rothman graduated from Sorbonne University and Paris-Diderot University, designing one of the very first word2matrix patented embedding and patented AI conversational agents. He began his career authoring one of the first AI cognitive natural language processing (NLP) chatbots applied as an automated language teacher for Moët et Chandon and other companies. He authored an AI resource optimizer for IBM and apparel producers. He then authored an advanced planning and scheduling (APS) solution used worldwide. mniej