This repository contains the code and corresponding data for the completion of three assignments in the "Applied Machine Learning" course. The analyses were conducted using Jupyter Notebooks, with detailed explanations of the steps taken to answer questions arising from data familiarization and the requirements of the assignments.
The focus of these assignments is primarily on data mining and analysis, as well as on the visualization of useful graphical representations. Each assignment's objective is to derive important conclusions based on the provided data and the course requirements.
These assignments were graded "Excellent" by the course instructor, indicating the high quality and rigor of the work.
data/: Contains the data files used in the analyses.- Jupiter Notebooks with corresponding names as the object of analysis
To run the code in this repository, you will need the following:
- Python (version >= 3.6)
- Jupyter Notebook
- Libraries such as pandas, numpy, matplotlib, and others as specified in the Notebooks
These assignments provide an in-depth exploration of data analysis and machine learning techniques, with a focus on practical applications. The detailed explanations within the Notebooks guide you through the process, from data exploration to final conclusions.
These assignments were graded "Excellent" by the course instructor, indicating the high quality and rigor of the work.