{"product_id":"hands-on-explainable-ai-xai-with-python-interpret-visualize-explain-and-integrate-reliable-ai-for-fair-secure-and-trustworthy-ai-apps-paperback","title":"Hands-On Explainable AI (XAI) with Python: Interpret, visualize, explain, and integrate reliable AI for fair, secure, and trustworthy AI apps - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eDenis Rothman\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eResolve the black box models in your AI applications to make them fair, trustworthy, and secure. Familiarize yourself with the basic principles and tools to deploy Explainable AI (XAI) into your apps and reporting interfaces.\u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eKey Features\u003c\/strong\u003e\u003c\/p\u003e \u003cul\u003e \u003cli\u003eLearn explainable AI tools and techniques to process trustworthy AI results\u003c\/li\u003e \u003cli\u003eUnderstand how to detect, handle, and avoid common issues with AI ethics and bias\u003c\/li\u003e \u003cli\u003eIntegrate fair AI into popular apps and reporting tools to deliver business value using Python and associated tools\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003cstrong\u003eBook Description\u003c\/strong\u003e\u003c\/p\u003e \u003cp\u003eEffectively 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.\u003c\/p\u003e \u003cp\u003eHands-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.\u003c\/p\u003e \u003cp\u003eYou 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.\u003c\/p\u003e \u003cp\u003eYou 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.\u003c\/p\u003e \u003cp\u003eBy the end of this AI book, you will possess an in-depth understanding of the core concepts of XAI.\u003c\/p\u003e \u003cp\u003e\u003cstrong\u003eWhat you will learn\u003c\/strong\u003e\u003c\/p\u003e \u003cul\u003e \u003cli\u003ePlan for XAI through the different stages of the machine learning life cycle\u003c\/li\u003e \u003cli\u003eEstimate the strengths and weaknesses of popular open-source XAI applications\u003c\/li\u003e \u003cli\u003eExamine how to detect and handle bias issues in machine learning data\u003c\/li\u003e \u003cli\u003eReview ethics considerations and tools to address common problems in machine learning data\u003c\/li\u003e \u003cli\u003eShare XAI design and visualization best practices\u003c\/li\u003e \u003cli\u003eIntegrate explainable AI results using Python models\u003c\/li\u003e \u003cli\u003eUse XAI toolkits for Python in machine learning life cycles to solve business problems\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003cstrong\u003eWho this book is for\u003c\/strong\u003e\u003c\/p\u003e \u003cp\u003eThis book is not an introduction to Python programming or machine learning concepts. You must have some foundational knowledge and\/or experience with machine learning libraries such as scikit-learn to make the most out of this book.\u003c\/p\u003e \u003cp\u003eSome of the potential readers of this book include: \u003c\/p\u003e \u003col\u003e \u003cli\u003eProfessionals who already use Python for as data science, machine learning, research, and analysis\u003c\/li\u003e \u003cli\u003eData analysts and data scientists who want an introduction into explainable AI tools and techniques\u003c\/li\u003e \u003cli\u003eAI Project managers who must face the contractual and legal obligations of AI Explainability for the acceptance phase of their applications\u003c\/li\u003e \u003c\/ol\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 454\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.92 x 9.25 x 7.5 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e July 30, 2020\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":52493561954611,"sku":"9781800208131","price":90.5,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0300\/5595\/6612\/files\/a0RrV2tiazBKZGpVWEp0dG5ZallsZz09.webp?v=1759957094","url":"https:\/\/www.vysn.com\/en-ca\/products\/hands-on-explainable-ai-xai-with-python-interpret-visualize-explain-and-integrate-reliable-ai-for-fair-secure-and-trustworthy-ai-apps-paperback","provider":"VYSN","version":"1.0","type":"link"}