Colorado Technical University Machine Learning Using Jupyter Notebook and Python

Description

Assignment Details:

Think of the difference between Supervised andUnsupervised as having supervising entity letting you know if you aremaking the right decisions, or not in the case of supervised. Theopposite would be true of unsupervised learning. Supervised learning maybenefit from label classifications of data such as flowers (roses,tulips, carnations, etc.). Where unsupervised may not have aclassification to benefit from as the answer to the question may be theaim.

Using the provided datasetthat represents the Titanic disaster, create both an unsupervisedclustering algorithm to describe the data and a simple supervisedclassification prediction to determine who might survive. Implement youralgorithms in Python.

Submit 2 Python files with roughly 50-80 lines of code each and 1 MS Word document (or Jupyter Notebook).

Code file must include a file header that includes the followinginformation at a minimum: Your name, date, course, and description ofthe code.
Code must be well-commented and in your own words. Explain your decisions and what the code is doing.
Code should adhere to best practice code standards.
Capture and record results and screenshots in a Word document.

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