Practical Linear Algebra for Data Professionals: Build unique solutions for your data science problems by coding linear algebra in Python - Couverture souple
Synopsis
Practical Linear Algebra for Data Professionals
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À propos des auteurs
Joe Ganser holds a masters in applied physics from Columbia University in NY. He was previously a physicist and worked on a Ph.D. in physics before going into data science. His current research interests have been in marketing analytics, algorithmic finance, quantum optics, and healthcare.
Abhinav Maurya is a research scientist at Amazon with research interests spanning artificial intelligence, machine learning, data science, computational social science, and AI strategy and policy. He has studied Computer Science and Engineering at IIT Bombay and Machine Learning and Public Policy at Carnegie Mellon University. In the past, he has worked at or collaborated with many cutting-edge technology corporations such as Microsoft, LinkedIn, Yelp, Uber, Robert Bosch GmbH, and IBM Research.
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