Think of the difference between Supervised and Unsupervised as having supervising entity letting you know if you are making the right decisions, or not in the case of supervised. The opposite would be true of unsupervised learning. Supervised learning may benefit from label classifications of data such as flowers (roses, tulips, carnations, etc.). Where unsupervised may not have a classification to benefit from as the answer to the question may be the aim.
Using the provided dataset that represents the Titanic disaster, create both an unsupervised clustering algorithm to describe the data and a simple supervised classification prediction to determine who might survive. Implement your algorithms 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 following information at a minimum: Your name, date, course, and description of the 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.
Here is the dataset that has to be used:
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