olgarozhdestvina/machine-learning-and-statistics-tasks

Task Assessment

Task Assessment for Machine Learning and Statistics Module GMIT 2020

The repository consists of four tasks covering various topics on Machine Learning and Statistics:

• Calculating square root of 2 to 100 decimal places without using Python libraries
• Verifying the Chi-squared value
• Python analysis of standard deviation in Microsoft Excel: STDEV.P vs STDEV.S
• Iris k-Nearest Neighbours

Submitted by: Olga Rozhdestvina (Student No: G00387844)

Lecturer: Ian McLoughlin

Programming Language used: Python

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Set up

Applications used for completion of the tasks are The Jupyter Notebook and cmder

Distribution of Python is Anaconda Python distribution.

Libraries used to complete the tasks: NumPy, Pandas, Matplotlib, Seaborn, SciPy, scikit-learn. All of these are installed with the Anaconda Python distribution.

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How to run the code

1. Make sure that you have Python installed
2. Download or clone current repository "Machine-Learning-and-Statistics-Tasks"
3. Open Command Interpreter and get into correct directory
4. Install packages by running pip install -r requirements.txt (recommended through virtual environment to avoid possible break of system tools or other projects)
5. Run Jupyter notebook
6. On the home page of opened Jupyter server select Tasks.ipynb

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License

This project is licensed under the MIT License - see the LICENSE.md file for details