Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.
Understand the principles and practices of machine learning and deep learning
This hands-on guide lays out machine learning and deep learning techniques and technologies in a style that is approachable, using just the basic math required. Written by a pair of experts in the field, Machine Learning and Deep Learning Using Python and TensorFlow contains case studies in several industries, including banking, insurance, e-commerce, retail, and healthcare. The book shows how to utilize machine learning and deep learning functions in today’s smart devices and apps. You will get download links for datasets, code, and sample projects referred to in the text.
Coverage includes:
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Venkata Reddy Konasani is a data scientist and corporate trainer with experience in credit risk modeling, market response model building, social media analytics, and machine learning and deep learning. He holds a Master's degree in applied statistics and informatics from IIT Bombay.
Shailendra Kadre works at Hewlett Packard and holds a master’s degree in mechanical engineering from IIT Delhi. He is the author of two books and numerous articles dealing with business analytics.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
Anbieter: moluna, Greven, Deutschland
Kartoniert / Broschiert. Zustand: New. Über den AutorVenkata Reddy Konasani is a data scientist and corporate trainer with experience in credit risk modeling, market response model building, social media analytics, and machine learning and deep learni. Artikel-Nr. 376980334
Anzahl: Mehr als 20 verfügbar
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Neuware - Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. Artikel-Nr. 9781260462296
Anzahl: 2 verfügbar