Machine Learning

  

Overview: Ever since the intersection of lightning-fast hardware and brilliant software, machines have been learning how to think like humans. Data scientists use many different kinds of machine learning algorithms to discover patterns in big data that lead to actionable insights. At a high level, these different algorithms can be classified into two groups based on the way they “learn” about data to make predictions: supervised and unsupervised learning. 

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 Explain the differences between the two main types of machine learning methods. 

 Describe how artificial neural nets (ANNs) use supervised learning to predict outcomes in decision-making. 

 Provide one real-world example of how each type of learning is applied in data science.
please find the attached file for more details. 

Data scienceBusiness Intelligence

Topic: Machine Learning

Overview: Ever since the intersection of lightning-fast hardware and brilliant software, machines have been learning how to think like humans. Data scientists use many different kinds of machine learning algorithms to discover patterns in big data that lead to actionable insights. At a high level, these different algorithms can be classified into two groups based on the way they “learn” about data to make predictions: supervised and unsupervised learning.

Explain the differences between the two main types of machine learning methods.

Describe how artificial neural nets (ANNs) use supervised learning to predict outcomes in decision-making.

Provide one real-world example of how each type of learning is applied in data science.

Guidelines for Submission: Using APA 6th edition style standards, submit a Word document that is 2-3 pages in length (excluding title page, references, and appendices) and include at least two credible scholarly references to support your findings. The UC Library is a good place to find these sources. Be sure to cite and reference your work using the APA guides and essay template that are located in the courseroom.

Include the following critical elements in your essay:

I. Supervised and Unsupervised learning: Explain the differences between the two main types of machine learning methods. What are the main categories of each learning method?

II. Artificial Neural Nets: Describe how artificial neural nets (ANNs) use supervised learning to predict outcomes in decision-making. How are ANNs employed as data analysis tools for forecasting in the realm of managerial decision support?

III. Real-world Examples: Provide a real-world example of each type of learning and explain how each method is applied in each of your examples. You should discuss one example of supervised learning and one example of unsupervised learning in this section of the essay.

Required elements:

Please ensure your paper complies APA 6th edition style guidelines.

APA basics: o Your essay should be typed, double-spaced on standard-sized paper (8.5″ x 11″) o Use 1″ margins on all sides, first line of all paragraphs is indented ½” from the margin o Use 12 pt. Times New Roman font

Follow the outline provided above and use section headers to improve the readability of your paper. If I cannot read and understand it, you will not earn credit for the content.

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