David Paper
Die Suchergebnisse bei Legimi sind auf die vom Nutzer angegebenen Suchkriterien zugeschnitten. Wir versuchen Titel, die für unsere Nutzer von besonderem Interesse sein könnten, durch die Bezeichnung "Bestseller" oder "Neuheit" hervorzuheben. Titel in der Liste der Suchergebnisse können auch sortiert werden - die Sortierauswahl hat Vorrang vor anderen Ergebnissen."

​Dr. Paper is a retired academic from the Utah State University (USU) Data Analytics and Management Information Systems department in the Huntsman School of Business. He has over 30 years of higher education teaching experience. At USU, he taught for 27 years in the classroom and distance education over satellite. He taught a variety of classes at the undergraduate, graduate, and doctorate levels, but he specializes in applied technology education.

Dr. Paper has competency in several programming languages, but his focus is currently on deep learning with Python in the TensorFlow-Colab Ecosystem. He has published extensively on machine learning, including Apress books:  Data Science Fundamentals for Python and MongoDB,  Hands-on Scikit-Learn for Machine Learning Applications: Data Science Fundamentals with Python, and  TensorFlow 2.x in the Colaboratory Cloud: An Introduction to Deep Learning on Google’s Cloud Service. He has also published more than 100 academic articles.

Besides growing up in family businesses, Dr. Paper has worked for Texas Instruments, DLS, Inc., and the Phoenix Small Business Administration. He has performed IS consulting work for IBM, AT&T, Octel, the Utah Department of Transportation, and the Space Dynamics Laboratory. He has worked on research projects with several corporations, including Caterpillar, Fannie Mae, Comdisco, IBM, RayChem, Ralston Purina, and Monsanto. He maintains contacts in corporations such as Google, Micron, Oracle, and Goldman Sachs.