The Machine Learning Pod (MLPod™) Canvas: An End-To-End Methodology to Design, Build, and Deploy ML Applications

In Mina Farmanbar, Maria Tzamtzi, Ajit Kumar Verma & Antorweep Chakravorty (eds.), Frontiers of Artificial Intelligence, Ethics, and Multidisciplinary Applications: 1st International Conference on Frontiers of AI, Ethics, and Multidisciplinary Applications (FAIEMA), Greece, 2023. Springer Nature Singapore. pp. 51-58 (2024)
  Copy   BIBTEX

Abstract

A methodology is introduced to assist the development of a product based on the Machine Learning technology. Augmenting the concept of the Business Model Canvas we propose a similar concept, named MLPod™ Canvas, that takes into consideration both technical and business requirements and assists the core product development team to clearly identify the tasks and the requirements for delivering a functional and compliant product. Hints regarding the completion of the canvas are also provided along with explanations about the purpose of each canvas’ individual block.

Links

PhilArchive



    Upload a copy of this work     Papers currently archived: 92,497

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Similar books and articles

From privacy to anti-discrimination in times of machine learning.Thilo Hagendorff - 2019 - Ethics and Information Technology 21 (4):331-343.
Inductive logic, verisimilitude, and machine learning.Ilkka Niiniluoto - 2005 - In Petr H’Ajek, Luis Vald’es-Villanueva & Dag Westerståhl (eds.), Logic, methodology and philosophy of science. London: College Publications. pp. 295/314.

Analytics

Added to PP
2024-03-02

Downloads
2 (#1,809,554)

6 months
2 (#1,206,551)

Historical graph of downloads

Sorry, there are not enough data points to plot this chart.
How can I increase my downloads?

Citations of this work

No citations found.

Add more citations

References found in this work

No references found.

Add more references