Examples of supervised machine learning algorithms may include linear regression, KNN, Naïve Bayes Classifiers, Decision tree, Neural Networks, …etc.

INSTRUCTIONS TO CANDIDATES

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Please read the instructor’s requirements and complete what I have already done. I have made 2.5 pages on “breast cancer detection using ML” as a midterm proposal and need your help to complete the final paper (I will send my work once we agree on the price). Therefore, I need from you 3 things:

1. Choose the best machine learning algorithm that would best fit on the datasrt of the topic.

Examples of supervised machine learning algorithms may include linear regression, KNN, Naïve Bayes Classifiers, Decision tree, Neural Networks, …etc. Examples of unsupervised machine learning may include K-Means clustering, mean-shift clustering…etc.

2. Apply the selected model on the data set (I will share the one I found).

3. Based on your analysis and results, complete the paperwork. 

The following is the instructor’s instructions:

In this final project, you are asked to work on one problem in healthcare that needs to be solved using sophisticated data analytics and machine learning approach. The project should have the needed data file before you choose to work on the project. 

I. A report with detailed information about your project, including the following sections (10-15 pages excluding references and title page, single space, 12-point Times New Roman, use as many references as you need in APA format)

a) Introduction (Background, Motivation, Objectives etc.)

b) The description of the specific problem and the data.

c) Methods for data analytics and machine learning (describing the approach and the justification for choosing this approach).

d) Evaluation methods for the obtained results.

e) Results (summary of the findings) and discussion (unsolved issues, interesting findings, limitations of the study, comparison with prior studies)

f) Conclusion

II. Source code (.ipynb files) and data used in the project

a) The source code should be able to run and generate the results described in the report.

 

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