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Application in Python Requires Lopeswrite Assessment Description It is essential in data science and related disciplines to understand how practical data science applications relate to real-world experiences

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Application in Python

Requires Lopeswrite

Assessment Description

It is essential in data science and related disciplines to understand how practical data science applications relate to real-world experiences.

 

Refer to the "16 Data Science Projects with Source Code to Strengthen your Resume," located in the topic Resources.

 

Choose one of the following data science projects in Python to review:

 

1. Detecting Fake News with Python and Machine Learning.
2. Detecting Parkinson’s Disease with XGBoost.
3. Gender and Age Detection with OpenCV.

 

Follow the steps to implement the code (source code is provided in each case) on your own computer.

 

Take appropriate screenshots (with descriptions) as needed.

 

All documentation should be completed in your Jupyter Notebook IPYNB file.

 

Then, answer the following questions:

 

1. What data sets/packages/libraries were used to implement the project? Why?
2. What visualizations were employed to delineate the data?
3. Why were these used compared to other options? How was the final project visualized (e.g., plot, visual report, etc.)? Do you feel this was the best way? Support your rationale.
4. What type of data science project idea do you feel would be worth conducting in your specific field or industry? Explain your choice.

 

Part 3

 

In 250-500 words, compare the nuances of working in R and Python based on the application assignments in Weeks 5 and 8. Make sure to discuss the advantages and disadvantages.

 

Deliverables

 

A Jupyter Notebook file to include appropriate screenshots (with descriptions).

 

Then, in 500-750 words, address the corresponding questions, as well as the comparisons between R and Python.

 

Make sure to justify your rationale using sound statistical arguments and associated formulas.

 

Prepare this assignment according to the guidelines found in the APA Style Guide, located in the Student Success Center.

An abstract is not required.

 

This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.

 

You are required to submit this assignment to LopesWrite.

A link to the LopesWrite technical support articles is located in Class Resources if you need assistance.

 

Reference

 

Statistical Techniques in Business and Economics

 

Lind, D., Marchal, W. and Wathen, S. (2020). Statistical techniques in business and economics (18th ed.). McGraw-Hill. ISBN-13: 9781260239478