Explainable AI Recipes: Implement Solutions to Model Explainability and

Description: Chapter 1: Introduction to Explainability Library InstallationsChapter Goal: This chapter is to understand various XAI library installations process and initialization of libraries to set up the explainability environment.No of pages: 15-20 pages Chapter 2: Linear Supervised Model ExplainabilityChapter Goal: This chapter aims at explaining the supervised linear models as regression and classification and related issues.No of pages: 20-25 Chapter 3: Non-Linear Supervised Learning Model ExplainabilityChapter Goal: This chapter explains the use of XAI libraries to explain the decisions made by non-linear models for regression and classification.No of pages : 20-25 Chapter 4: Ensemble Model for Supervised Learning ExplainabilityChapter Goal: This chapter explains the use of XAI to explain the decisions made by ensemble models in regression and classification scenarios.No of pages: 20-25 Chapter 5: Explainability for Natural Language ModelingChapter Goal: In this chapter, we are going to use XAI for natural language processing, pre-processing, and feature engineering. No of pages: 15-20 Chapter 6: Time Series Model ExplainabilityGoal: The objective of this chapter is to explain the forecast using XAI libraries No of Pages: 10-15 Chapter 7: Deep Neural Network Model ExplainabilityGoal: Using XAI libraries to explain the decisions made by Deep Learning modelsNo of Pages: 20-25

Price: 57.92 AUD

Location: Hillsdale, NSW

End Time: 2024-11-04T17:03:10.000Z

Shipping Cost: 32.76 AUD