Machine learning (ML)

Description
Python, R programming languages are an extension of previous versions of other common languages such as Algol 60, Pascal, and Modula 2, etc. It includes excellent facilities. Python and R languages support some packages of public tools for Machine learning (ML).

1. Select and study two datasets/Big datasets from any data repository or real data such as (Images or text files, web contents, social media data, videos, etc.
2. Select and study two appropriate ML algorithms with exceptions the decision trees.
3. Mention the function of the algorithms and put the purpose of the dataset you selected, its source and its attributes
4. Identify the objective for the dataset analysis.
5. Analyze the data using the selected algorithms
6. Apply many experiments using the selected algorithms on that dataset to get better results.
7. Write a report contains a full description for the following:
8. Explanation of Machine learning algorithms with Python 1 page
9. Explanation of Machine learning algorithms with R language 1 page
10. Write a comparison of Python and R, the functionalities, similarities and difference 1 page
11. Explain the data pre-processing steps.
12. Explain the data analysis step by step (only for one or two experiments).
13. Present the Results in tables + explain each table in detail.
14. Visualize the results using graphics with an explanation of each graph separately
15. Interpret and discus the results deeply.
16. State recommendations for further improvements
17. Write conclusions ½ page
18. List a New Reference list for Python and R, etc [6 to 8]

 
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