Question

Why does AI project cycle often become cyclic in nature?

Answer 1

Answer:

Artificial Intelligence (AI) is an interdisciplinary branch of computer science, which saw decades of research and development before it was commercialized as a technology. This technology focuses on making computer systems perform tasks that would normally require a human being.

AI involves “training” computer systems on tasks using “experience”, and the “experience” is obtained from a massive amount of data. As more data is fed to the computer system, it “learns” more and performs the task better. Read “Artificial intelligence | what is it and why it matters” for more insights.

AI has use cases in several sectors like agriculture, banking, healthcare, manufacturing, retail, etc., moreover, it can transform various functions like customer service, fraud prevention, etc. Not surprisingly, the global market of AI is growing significantly. Your organization could benefit from AI too!

This market will likely reach $190.61 billion by 2025. A MarketsandMarkets research report states that the global AI market will have a CAGR of 36.62% during the 2018-2025 period.

Answer 2

The machine learning life cycle is the cyclical process that data science projects follow. It defines each step that an organization should follow to take advantage of machine learning and artificial intelligence (AI) to derive practical business value.

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