This content is part of the Essential Guide: A machine learning and AI guide for enterprises in the cloud
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Quiz: Find out how smart you are about machine learning and AI

Machine learning can help businesses gain powerful analytics value from their data -- but only if it's done right. How much do you know about machine learning and related forms of AI?

Machine learning and artificial intelligence have become mainstream methods of data analytics in the business world. And it's easy to see why: They enable businesses to create automated analytics engines that are capable of powering their way through large data sets, providing information not otherwise available and freeing up data scientists and analysts to work on more projects.

But that doesn't mean machine learning and artificial intelligence (AI) initiatives are easy. While machine learning is an effective analytics technique when used correctly, there are big obstacles to implementing it and its related approaches, such as deep learning and the use of AI chatbots. Such complex analytics applications require in-depth data science skills, heavy amounts of data preparation work and a robust big data infrastructure -- a combination of needs that makes it a challenge for many businesses to begin using AI-based technologies.

Are you ready to take on machine learning and AI in your organization? Find out by taking this quiz -- and discover some helpful articles along the way with insight and advice to help you better understand these technologies and how to succeed with them.

Next Steps

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How are you using machine learning, deep learning and other forms of AI at your company?
Questions 3 and 6 have 2 possible answers TBH :)
Question 8 answer is wrong. I have performed many ML tasks with less than 1 GB of data. The data does not always require a Hadoop system for the answers. A laptop will do.
Agree completely - Hadoop is free and easy to setup making it ideal for starters and experts.  Having the appropriate amount and type of data is the biggest issue I have encountered - it does not have to be vast.