Table of Contents

Chapter 1:  Introduction to Explainability Library Installations.- Chapter 2:  Linear Supervised Model Explainability.- Chapter 3: Non-Linear Supervised Learning Model Explainability.- Chapter 4: Ensemble Model for Supervised Learning Explainability.- Chapter 5: Explainability for Natural Language Modeling.- Chapter 6: Time Series Model Explainability.- Chapter 7: Deep Neural Network Model Explainability.

About the Author

Pradeepta Mishra is the Director of AI, Fosfor at L&T Infotech (LTI). He leads a large group of data scientists, computational linguistics experts, and machine learning and deep learning experts in building the next-generation product—Leni—which is the world’s first virtual data scientist. He has expertise across core branches of artificial intelligence, including autonomous ML and deep learning pipelines, ML ops, image processing, audio processing, natural language processing (NLP), natural language generation (NLG), design and implementation of expert systems, and personal digital assistants (PDAs). In 2019 and 2020, he was named one of "India's Top 40 Under 40 Data Scientists" by Analytics India magazine. Two of his books have been translated into Chinese and Spanish, based on popular demand. 
Pradeepa delivered a keynote session at the Global Data Science Conference 2018, USA. He delivered a TEDx talk on "Can Machines Think?", available on the official TEDx YouTube channel. He has mentored more than 2,000 data scientists globally. He has delivered 200+ tech talks on data science, ML, DL, NLP, and AI at various universities, meetups, technical institutions, and community-arranged forums. He is a visiting faculty member to more than 10 universities, where he teaches deep learning and machine learning to professionals, and mentors them in pursuing a rewarding career in artificial intelligence.