{"product_id":"139462","title":"XAI Explainable Artificial Intelligence: Dissecting Artificial Intelligence ","description":"\u003ccenter\u003e\u003cdiv style=\"text-align:center\"\u003e\u003cimg src=\"https:\/\/tmgdisk01.cafe24.com\/images\/vs\/4172\/sv\/3jXPBvoVFGKLvSADMoCo2RCXMA2Z2l.png?v=1765074976\" style=\"max-width:100%;max-height:10px\"\u003e\u003c\/div\u003e\u003c\/center\u003e\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\u003ccenter\u003e\n\n\u003cdiv style=\"width:95%\"\u003e\n\n\u003cdiv style=\"text-align:center;font-size:30px;font-weight:bolder;line-height:1.6em\"\u003e XAI: Explainable Artificial Intelligence, Dissecting Artificial Intelligence \u003c\/div\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003cdiv style=\"border-bottom:1px;border-bottom-style:dotted;border-color:;padding-bottom:20px\"\u003e\u003ccenter\u003e\u003ctable align=\"center\" width=\"100%\"\u003e\u003ctbody style=\"border:0px\"\u003e\n\n\u003ctr\u003e\u003ctd align=\"center\" style=\"line-height:1.2em;text-align:center;font-size:18px;color:black;font-weight:bold;padding-bottom:20px;\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\n\n\u003ctr\u003e\u003ctd style=\"text-align:center\"\u003e\u003cimg src=\"https:\/\/image.yes24.com\/goods\/89583774\/XL\" style=\"max-width:100%;height:auto\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\n\n\n\u003c\/tbody\u003e\u003c\/table\u003e\u003c\/center\u003e\u003c\/div\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003cdiv style=\"width:95%;{split_style6}padding-top:20px;padding-bottom:20px\"\u003e\n\n\u003cdiv style=\"text-align:left;font-size:16px;font-weight:bold;padding-bottom:20px\"\u003e Description \u003c\/div\u003e\n\n\u003cdiv style=\"text-align:left;word-break:break-all;font-size:14px;line-height:1.6em;\"\u003e\n\n\u003cdiv\u003e\u003ch5\u003e \u003cb\u003eBook Introduction\u003c\/b\u003e\n\u003c\/h5\u003e\u003c\/div\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e\u003cdiv\u003e XAI (eXplainable Artificial Intelligence) is a research field that explains the reasons for artificial intelligence's judgment, and its necessity is increasing as artificial intelligence technology expands.\u003cbr\u003e This contrasts with \"black box\" AI, where even the algorithm's designers cannot explain the rationale behind the AI's decisions. XAI eliminates the uncertainty surrounding AI's decision-making process, thereby increasing its reliability.\u003cbr\u003e \u003cbr\u003eThis book covers XAI techniques applicable to traditional machine learning techniques as well as those applicable to cutting-edge deep learning models. Because XAI is a technology that infers the reasons behind AI's decision-making, the process of applying the techniques is as important as the theory itself.\u003cbr\u003e Therefore, this book includes example code that was not covered in existing XAI books.\u003cbr\u003e First, you can learn the theory and then follow the code corresponding to the theory to directly check the XAI analysis results without a separate installation process.\u003cbr\u003e\n\u003c\/div\u003e\u003c\/div\u003e\n\u003cdiv\u003e\u003cul\u003e\u003cli\u003e You can preview some of the book's contents.\u003cbr\u003e \u003cspan\u003ePreview\u003c\/span\u003e\n\n\u003c\/li\u003e\u003c\/ul\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cbr\u003e\u003cdiv\u003e\u003ch5\u003e \u003cb\u003eindex\u003c\/b\u003e\n\u003c\/h5\u003e\u003c\/div\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e \u003cb\u003e▣ Chapter 1: Opening the Story\u003c\/b\u003e\u003cbr\u003e 1.1.\u003cbr\u003e DARPA's innovation project\u003cbr\u003e 1.2. XAI (2016-2021)\u003cbr\u003e 1.3. Conditions for doing XAI well\u003cbr\u003e ___1.3.1.\u003cbr\u003e Have a thorough understanding of existing machine learning theory\u003cbr\u003e ___1.3.2.\u003cbr\u003e Thinking about how to graft the explanation model\u003cbr\u003e 1.4.\u003cbr\u003e XAI and Deep Learning XAI using xgboost?\u003cbr\u003e 1.5. \u003cbr\u003eThank you\u003cbr\u003e\u003cbr\u003e \u003cb\u003e▣ Chapter 2: Building a Practice Environment\u003c\/b\u003e\u003cbr\u003e 2.1.\u003cbr\u003e Install Python\u003cbr\u003e 2.2. Installing PIP\u003cbr\u003e 2.3.\u003cbr\u003e Installing TensorFlow\u003cbr\u003e 2.4.\u003cbr\u003e Jupyter Notebook\u003cbr\u003e 2.4.1.\u003cbr\u003e Verify Tensorflow-GPU installation\u003cbr\u003e\u003cbr\u003e \u003cb\u003e▣ Chapter 3: Preparing for XAI Development\u003c\/b\u003e\u003cbr\u003e 3.1.\u003cbr\u003e Understanding Machine Learning\u003cbr\u003e 3.2.\u003cbr\u003e A peek inside the black box\u003cbr\u003e 3.3.\u003cbr\u003e Understanding the Difference Between Visualization and XAI\u003cbr\u003e\u003cbr\u003e \u003cb\u003e▣ Chapter 4: Decision Tree\u003c\/b\u003e\u003cbr\u003e 4.1.\u003cbr\u003e Decision Tree Visualization\u003cbr\u003e 4.2.\u003cbr\u003e Finding feature importance\u003cbr\u003e 4.3.\u003cbr\u003e Drawing a partial dependence plot (PDP)\u003cbr\u003e 4.4. Using XGBoost\u003cbr\u003e ___4.4.1. Advantages of XGBoost\u003cbr\u003e ___4.4.2. XGBoost is not deep learning\u003cbr\u003e ___4.4.3.\u003cbr\u003e Basic principles\u003cbr\u003e ___4.4.4.\u003cbr\u003e Parameters\u003cbr\u003e ___4.4.5.\u003cbr\u003e Actual Actions and Tips\u003cbr\u003e 4.5.\u003cbr\u003e Exercise 1: Pima Indian Diabetes Decision Model\u003cbr\u003e ___4.5.1.\u003cbr\u003e Learn\u003cbr\u003e ___4.5.2.\u003cbr\u003e Combining explainable models\u003cbr\u003e ___4.5.3.\u003cbr\u003e Tuning the model\u003cbr\u003e ___4.5.4.\u003cbr\u003e In conclusion\u003cbr\u003e\u003cbr\u003e \u003cb\u003e▣ Chapter 5: Proxy Analysis\u003c\/b\u003e\u003cbr\u003e 5.1.\u003cbr\u003e Introduction to Proxy Analysis\u003cbr\u003e ___5.1.1.\u003cbr\u003e Global Proxy Analysis\u003cbr\u003e ___5.1.2.\u003cbr\u003e Local Surrogate Analysis\u003cbr\u003e 5.2. LIME\u003cbr\u003e ___5.2.1. Understanding the LIME Algorithm Intuitively\u003cbr\u003e ___5.2.2.\u003cbr\u003e Background theory  \u003cbr\u003e___5.2.3.\u003cbr\u003e Exercise 2: Applying LIME to Text Data\u003cbr\u003e ___5.2.4.\u003cbr\u003e Exercise 3: Applying LIME to Image Data\u003cbr\u003e ___5.2.5.\u003cbr\u003e In conclusion\u003cbr\u003e 5.3. SHAP (SHapley Additive exPlanations)\u003cbr\u003e ___5.3.1.\u003cbr\u003e Background theory\u003cbr\u003e ___5.3.2.\u003cbr\u003e Exercise 4: Using Shapley Values ​​in a Sharing Economy Startup\u003cbr\u003e ___5.3.3.\u003cbr\u003e Exercise 5: Finding the Determinants of Boston Housing Prices\u003cbr\u003e ___5.3.4.\u003cbr\u003e In conclusion\u003cbr\u003e\u003cbr\u003e \u003cb\u003e▣ Chapter 6: Filter Visualization\u003c\/b\u003e\u003cbr\u003e 6.1.\u003cbr\u003e Image filter visualization\u003cbr\u003e 6.2.\u003cbr\u003e Combining explainable models\u003cbr\u003e ___6.2.1.\u003cbr\u003e Convolutional neural networks and filters\u003cbr\u003e 6.3.\u003cbr\u003e Building a Convolutional Neural Network\u003cbr\u003e 6.4.\u003cbr\u003e Exercise 6: Visualizing Convolutional Neural Networks\u003cbr\u003e ___6.4.1.\u003cbr\u003e Visualize input values ​​and compare them with predicted values\u003cbr\u003e ___6.4.2.\u003cbr\u003e Filter visualization\u003cbr\u003e 6.5.\u003cbr\u003e In conclusion\u003cbr\u003e\u003cbr\u003e \u003cb\u003e▣ Chapter 07: LRP (Layer-wise Relevance Propagation)\u003c\/b\u003e\u003cbr\u003e 7.1.\u003cbr\u003e Background theory\u003cbr\u003e ___7.1.1.\u003cbr\u003e Decomposition\u003cbr\u003e ___7.1.2.\u003cbr\u003e propagation of validity\u003cbr\u003e 7.2.\u003cbr\u003e Exercise 7: Unpacking Convolutional Neural Networks\u003cbr\u003e ___7.2.1.\u003cbr\u003e Training a Convolutional Neural Network\u003cbr\u003e ___7.2.2.\u003cbr\u003e Obtaining a convolutional neural network subgraph\u003cbr\u003e ___7.2.3. \u003cbr\u003eApplying LRP to Convolutional Neural Networks\u003cbr\u003e ___7.3. Trends in Deep Learning XAI Before and After the Emergence of LRP\u003cbr\u003e 7.4.\u003cbr\u003e In conclusion\u003cbr\u003e\u003cbr\u003e \u003cb\u003e▣ Chapter 8: Practical Analysis 1: Decision Trees and XAI\u003c\/b\u003e\u003cbr\u003e 8.1.\u003cbr\u003e Creating AI for Credit Loan Analysis\u003cbr\u003e ___8.1.1.\u003cbr\u003e Data Description\u003cbr\u003e ___8.1.2.\u003cbr\u003e Column Description\u003cbr\u003e ___8.1.3.\u003cbr\u003e Loading data\u003cbr\u003e ___8.1.4.\u003cbr\u003e Learning data\u003cbr\u003e 8.2. Combining XAI\u003cbr\u003e 8.3. Understanding the Model with XAI\u003cbr\u003e 8.4. Establishing a Basis for Model Improvement with XAI\u003cbr\u003e\u003cbr\u003e \u003cb\u003e▣ Chapter 9: Practical Analysis 2: LRP and XAI\u003c\/b\u003e\u003cbr\u003e 9.1.\u003cbr\u003e Building a Sentiment Analysis Model\u003cbr\u003e ___9.1.1.\u003cbr\u003e Data Description\u003cbr\u003e ___9.1.2.\u003cbr\u003e Column Description\u003cbr\u003e ___9.1.3.\u003cbr\u003e Loading data\u003cbr\u003e ___9.1.4.\u003cbr\u003e Learning data\u003cbr\u003e 9.2. Combining XAI\u003cbr\u003e 9.3. Improving the Original AI with XAI\u003cbr\u003e 9.4.\u003cbr\u003e Notice\u003cbr\u003e\u003cbr\u003e \u003cb\u003e▣ Chapter 10: Closing the Story\u003c\/b\u003e\u003cbr\u003e 10.1.\u003cbr\u003e Finding Dark Matter\u003cbr\u003e 10.2.\u003cbr\u003e Adding XAI to existing models\u003cbr\u003e 10.3. The Future of XAI\u003cbr\u003e\u003cbr\u003e \u003cb\u003e▣ Chapter 11: References\u003c\/b\u003e\u003cbr\u003e 11.1. Installing the XAI Practice Library\u003cbr\u003e ___11.1.1.\u003cbr\u003e Install Python\u003cbr\u003e ___11.1.2.\u003cbr\u003e Installing Python Libraries\u003cbr\u003e ___11.1.3.\u003cbr\u003e Installing TensorFlow\u003cbr\u003e 11.2. \u003cbr\u003eCandlestick chart\u003cbr\u003e 11.3.\u003cbr\u003e confusion matrix\u003cbr\u003e ___11.3.1.\u003cbr\u003e Accuracy\u003cbr\u003e ___11.3.2.\u003cbr\u003e Precision\u003cbr\u003e ___11.3.3.\u003cbr\u003e Sensitivity (or Recall)\u003cbr\u003e ___11.3.4.\u003cbr\u003e Specificity\u003cbr\u003e ___11.3.5.\u003cbr\u003e Fallout rate\u003cbr\u003e ___11.3.6.\u003cbr\u003e F1-score\u003cbr\u003e 11.4.\u003cbr\u003e TensorFlow Slim\u003cbr\u003e 11.5.\u003cbr\u003e Normalization\u003cbr\u003e\n\u003c\/div\u003e\n\u003cdiv\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cbr\u003e\u003cdiv\u003e\u003ch5\u003e \u003cb\u003eDetailed image\u003c\/b\u003e \u003c\/h5\u003e\u003c\/div\u003e\n\u003cdiv\u003e\u003cdiv\u003e\u003cimg src=\"https:\/\/image.yes24.com\/momo\/TopCate2996\/MidCate005\/299545119.jpg\" border=\"0\" alt=\"Detailed Image 1\"\u003e\u003c\/div\u003e\u003c\/div\u003e\n\u003cbr\u003e\u003cdiv\u003e\u003ch5\u003e \u003cb\u003ePublisher's Review\u003c\/b\u003e\n\u003c\/h5\u003e\u003c\/div\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e \u003cb\u003e★ What this book covers ★\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e ◎ Feature Importance\u003cbr\u003e ◎ Partial dependence plot\u003cbr\u003e ◎ Building an XGBoost model\u003cbr\u003e ◎ LIME (Local Interpretable Model-agnostic Explanations)\u003cbr\u003e ◎ SHAP (SHapley Additive exPlanations)\u003cbr\u003e ◎ Filter visualization\u003cbr\u003e ◎ Building a convolutional neural network (CNN)\u003cbr\u003e ◎ LRP (Layer-wise Relevance Propagation)\u003cbr\u003e ◎ Practical Analysis 1: Building and Explaining a Credit Loan Analysis Model\u003cbr\u003e ◎ Practical Analysis 2: Building and Explaining a Photo Sentiment Analysis Model\u003cbr\u003e\n\u003c\/div\u003e\n\u003cdiv\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003cdiv style=\"width:95%;padding-top:20px;padding-bottom:20px\"\u003e\n\n\u003cdiv style=\"text-align:left;font-size:16px;font-weight:bold;padding-bottom:20px\"\u003e GOODS SPECIFICS \u003c\/div\u003e\n\n\u003cdiv style=\"text-align:left;font-size:14px;line-height:1.6em;\"\u003e\n\n\u003cdiv style=\"width:100%;margin-bottom:5px;line-height:1.6em;font-size:14px\"\u003e - \u003cstrong\u003eDate of issue:\u003c\/strong\u003e March 27, 2020\u003c\/div\u003e\n\n\u003cdiv style=\"width:100%;margin-bottom:5px;line-height:1.6em;font-size:14px\"\u003e - \u003cstrong\u003ePage count, weight, size:\u003c\/strong\u003e 340 pages | 175*235*18mm\u003c\/div\u003e\n\n\u003cdiv style=\"width:100%;margin-bottom:5px;line-height:1.6em;font-size:14px\"\u003e - \u003cstrong\u003eISBN13:\u003c\/strong\u003e 9791158392000\u003c\/div\u003e\n\n\u003cdiv style=\"width:100%;margin-bottom:5px;line-height:1.6em;font-size:14px\"\u003e - \u003cstrong\u003eISBN10:\u003c\/strong\u003e 1158392001 \u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\u003ccenter\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e \n\u003cspan\u003e\u003c\/span\u003e\n\n\u003c\/center\u003e\n\n\n\u003c\/center\u003e","brand":"LIBRAIRIE COREENNE","offers":[{"title":"Default Title","offer_id":43893357248554,"sku":"139462","price":38.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0683\/2750\/5962\/files\/f0f7f073e84bdcc5dfa54b017f2a89ef.jpg?v=1765398265","url":"https:\/\/librairie.coreenne.fr\/en\/products\/139462","provider":"LIBRAIRIE COREENNE","version":"1.0","type":"link"}