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Artificial Intelligence Free Practice Test

Artificial Intelligence is the hottest buzzword in today’s world of technology. With the AI industry being very new and continuously expanding, making a career in AI can be a great option. If you are interested in making a career in AI, take this test and explore our different Artificial Intelligence courses. We highly recommend you to take this test.

  1. 5 questions in all, you need to score at least 70% to pass.
  2. You can retake the test at any time. We recommend you share it with friends.
Improve Your Artificial Intelligence Skills

#1. How do Google, Amazon, and LinkedIn use artificial intelligence in their ecosystems?

In case of LinkedIn, machine learning helps the platform and enhances the reach of jobs to the right people. Also, it helps in keeping track of the talent pool. Google uses AI in Vision API and Google Translate. Amazon uses AI in Alexa, Brainier Cloud, and AI Everywhere.

#2. How can AI enhance throughput and efficiency?

Self-driving cars have a combination of sensors, cameras, radar, and artificial intelligence technology. They are capable of sensing the environment and navigating without any human intervention.

#3. Which of the following is a formalization of relationships between variables in the form of mathematical equations?

Statistical analysis involves collecting and scrutinizing the data sample to identify trends. A statistical model is a formalization of relationships between variables in the form of mathematical equations.

#4. Train the Model is the first step of this type of machine learning. Identify the type.

Semi-supervised learning is when the training data includes some of the desired outputs. It is a hybrid approach and a combination of supervised and unsupervised learning. It uses a combination of labeled and unlabeled data.

#5. Which of the following is used in classification problems where the output can be of two or more types of classes?

The confusion matrix is one of the most intuitive and easiest matrix used to find correctness and accuracy of machine learning models. It is used in classification problems where the output can be of two or more types of classes.

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Improve Your Artificial Intelligence Skills


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