Explainable Artificial Intelligence: An Introduction to Interpretable Machine Learning

,

Éditeur :

Springer

Paru le : 2021-12-15

This book is written both for readers entering the field, and for practitioners with a background in AI and an interest in developing real-world applications. The book is a great resource for practitioners and researchers in both industry and academia, and the discussed case studies and associated m...
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Éditeur

Collection
n.c

Parution
2021-12-15

Pages
310 pages

EAN papier
9783030833558

Auteur(s) du livre


Uday Kamath has spent more than two decades developing analytics products in statistics, optimization, machine learning, NLP and speech recognition, and explainable AI. Uday has a Ph.D. in scalable machine learning and has contributed to many journals, conferences, and books in the field of AI. He is the author of books such as Deep Learning for NLP and Speech Recognition, Mastering Java Machine Learning, and Machine Learning: End-to-End Guide for Java Developers. He held many senior roles: Chief Analytics Officer for Digital Reasoning, Advisor for Falkonry, and Chief Data Scientist for BAE Systems Applied Intelligence. He has built products and solutions using AI in surveillance, compliance, cybersecurity, financial crime, anti-money laundering, and insurance fraud. Uday currently works as the Chief Analytics Officer for Smarsh. He is responsible for Data Science, research of analytics products employing deep learning and explainable AI, and modern techniques in speech and text used in the financial domain and healthcare.John Chih Liu, PhD, CFA is Chief Executive Officer of Intelluron Corporation. Previously, he held senior executive roles overseeing quantitative research, portfolio management and data science organizations, including as VP of Data Science, Applied Machine Learning at Digital Reasoning Systems, MD of Equity Strategies at the Vanderbilt University endowment, and Head of Index Options Trading at BNP Paribas. He is a frequent speaker and published author on topics including natural language processing, reinforcement learning, asset allocation, systemic risk and EM theory. John was named Nashville's Data Scientist of the Year in 2016, Finalist for Community Leader of the Year in 2018, and Finalist for Innovator of the Year in 2020. He earned his B.S., M.S., and Ph.D. in electrical engineering from the University of Pennsylvania and is a CFA Charterholder, advocate for the global data science community and supporter of the International Science and Engineering Fair.

Caractéristiques détaillées - droits

EAN PDF
9783030833565
Prix
137,14 €
Nombre pages copiables
3
Nombre pages imprimables
31
Taille du fichier
12093 Ko
EAN EPUB
9783030833565
Prix
137,14 €
Nombre pages copiables
3
Nombre pages imprimables
31
Taille du fichier
55767 Ko

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