Explain what is a parametric machine learning algorithm

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Artificial Intelligence Assignment: Machine Learning

Context/overview:

Artificial Intelligence is umbrella term under which we can find a term Machine Learning. Machine Learning can be done through the set of techniques that will create mathematical algorithms from the collected data, and by doing so, enable computers to make intelligent decisions.
For example, if we have a function F, than Machine Learning algorithms can be described as teaching (learning) a function F to best map input variable x to a output variable y.

Y= F(x)

Specific questions or items to address:

1. Describe what is the Machine Learning , and what is the difference between Machine Learning and Data mining. Provide a real world example of machine learning in action, and explain how it is used.

2. Explain what is a parametric machine learning algorithm and how is it different from a nonparametric machine learning algorithm

3. Provide and explain 3 examples of parametric machine learning algorithm

4. Provide and explain 3 examples of nonparametric machine learning algorithms

5. Discuss which of those 2 algorithm types are more accurate and more flexible

6. Describe the bias and variants, and provide the example of low /high bias algorithm. Justify your answer, explaining why is your example, an example of low/high bias algorithm

Criteria: (# pages, APA format, etc.)

Your document should adhere to the following:

• Please submit your document in a Word or Google doc (.docx file format)

Your document should have the following elements:

• Title page
• Course number and name
• Project name
• Student name
• Date
• Pages with content addressing the questions asked
• Reference page
• Deliverable Length: 2-5 pages (Not including title and reference page)
• Name the document "yourname_CS411_IP4.docx

Adhere to APA formatting and reference guidelines when writing your response. Additionally, your response should be free of grammatical errors, use complete sentences, and give specific details to support statements.

Reference no: EM131486443

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