AIF Dumps With Exact Questions and Answers

Collaboration, learning, and iterative are terms used to describe agile projects. Agile projects are designed to be adaptive and flexible, allowing teams to incorporate feedback and learn from their mistakes. This process encourages collaboration between team members, and emphasizes the importance of iterative development and continual improvement. Agile projects focus on delivering value quickly and efficiently, allowing teams to make changes and adapt to changing customer needs.

References: [1] https://www.bcs.org/upload/pdf/foundation-certificate-ai-syllabus-v1.pdf  [2] https://www.apmg-international.com/en/qualifications-and-certifications/bc-foundation-certificate-in-artificial-intelligence/  [3] https://www.exin.com/en/certifications/bc-foundation-certificate-in-artificial-intelligence/  [4] https://www.scrumguides.org/scrum-guide.html

In an AI project, a domain expert is a person with special knowledge or skills in that particular area of endeavour, and they are responsible for defining what is "fit for purpose" for the project. The domain expert provides insights into the problem and suggests ways to address it. They also provide guidance on evaluating and validating the AI system and its outputs. The domain expert is also responsible for communicating with stakeholders and providing feedback on the progress of the project. References:

• BCS Foundation Certificate In Artificial Intelligence Study Guide (2019), AI & People, Chapter 12.
• https://www.apmg-international.com/en/al-adoption/domain-expert/

TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers pushthe state-of-the-art in ML and developers easily build and deploy ML powered applications.

https://www.tensorflow.org/#:~:text=T ensorFlow%20is%20an%20end%2Dto,and%20deploy%20ML%20powered%20applications.

TensorFlow is an open source machine learning library created by Google. It is used for dataflow programming and is widely used for a variety of applications, including machine learning and deep learning. TensorFlow enables developers to build, train and deploy machine learning models easily and quickly. It has built-in support for a variety of deep learning frameworks, such as convolutional neural networks, recurrent neural networks, and autoencoders.

For more information, please refer to the BCS Foundation Certificate In Artificial Intelligence Study Guide (https://www.bcs.org/upload/pdf/bcs-foundation-certificate-in-artificial-intelligence-study-guide.pdf)  or the EXIN Artificial Intelligence Foundation Certification (https://www.exin.com/en/exams/artificial-intelligence-foundation).