古老
发表于 2025-3-26 22:24:12
http://reply.papertrans.cn/103/10296/1029514/1029514_31.png
arsenal
发表于 2025-3-27 01:51:55
http://reply.papertrans.cn/103/10296/1029514/1029514_32.png
微不足道
发表于 2025-3-27 07:08:09
http://reply.papertrans.cn/103/10296/1029514/1029514_33.png
老人病学
发表于 2025-3-27 11:38:44
Heiner Abelstecture for development, sharing, and deploying a machine learning solution. This book simplifies the process of choosing the right architecture and tools for doing machine learning based on your specific infrastructure needs and requirements. ..Detailed content is provided on the main algorithms fo
运动性
发表于 2025-3-27 17:13:04
Heiner Abelsing thisbook, you will understand how to use PySpark’s machine learning library to build and train various machine learning models. Additionally you’ll become comfortable with related PySpark components, such as data ingestion, data processing, and data analysis, that you can use to develop data-dri
Fibroid
发表于 2025-3-27 19:43:05
http://reply.papertrans.cn/103/10296/1029514/1029514_36.png
煞费苦心
发表于 2025-3-27 23:19:09
Heiner Abelsfor audit managers and directors. With the knowledge in this book, you can leverage simple concepts that are beyond mere buzz words to practice innovation in your team. You can build your credibility and trust 978-1-4842-8050-8978-1-4842-8051-5
monologue
发表于 2025-3-28 02:20:44
Heiner AbelsFlow offers a toolset that can be used to define and solve any graph-based model, including those commonly used in economics. This book is structured to teach through a sequence of complete examples, each frame978-1-4842-6372-3978-1-4842-6373-0
抵押贷款
发表于 2025-3-28 10:17:41
Heiner Abelsre textbooks..General purposes and scientific questions of the methods are only briefly mentioned, but full attention is given to the technical details. The two authors, a statistician and current president of 978-3-319-04180-3978-3-319-04181-0Series ISSN 2191-544X Series E-ISSN 2191-5458
DEAF
发表于 2025-3-28 13:25:43
Heiner Abelsr machine learning on geodata. It presents the basics of working with spatial data and advanced applications. Examples are presented using code (accessible at github.com/Apress/machine-learning-geographic-data978-1-4842-8286-1978-1-4842-8287-8