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1. Explain the differences between the two main types of machine learning methods.
2. Describe how artificial neural nets (ANNs) use supervised learning to predict outcomes in decision-making.
3. Provide one real-world example of how each type of learning is applied in data science.
The below criteria need to be fulfilled for the questions and need be in 600 words.
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 contest.
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