Reference no: EM134000537

Artificial Intelligence and Machine Learning

Assessment - Group simulation and problem solving using fundamental machine learning models

Task
Utilising either Orange Data Mining or Python, develop both supervised and unsupervised basic machine learning models to address real-world problems. Respond to the accompanying questions with thoughtful analysis. While collaboration with your group members is encouraged, you must independently design and implement your machine learning workflows and provide your answers.

Assessment Description

Throughout our exploration of machine learning, we have covered fundamental models such as logistic regression, k-NN, decision trees, k-means clustering, and principal component analysis. These models serve as the foundation for building analytics workflows using tools like Orange Data Mining or Python.

In this assessment, you will apply these basic machine learning models to real-world datasets, demonstrating their practical use in solving real-world problems (SLO 1). You will analyse the characteristics of each model, assess their effectiveness, and engage in problem-solving exercises that challenge your understanding (SLO 2). No AI shortcuts — Get genuine assignment help from experienced, real tutors.

Assessment Instructions

Working collaboratively in your group, use Orange Data Mining or Python to implement machine learning workflows to solve real-world problems. The datasets, parameters, and instructions are provided in the assessment sheet.

Based on software outputs, answer the accompanying questions in the assessment sheet. Some of the questions might require some manual calculations. Be sure to show all your workings; each step you take to reach your answer should be clearly presented. Provide any software screenshots (figures, tables) to justify your answer.

As a group, write a 1000-word (maximum) report that includes the specific answers to each question from the assessment sheet.

Your Task

Utilising either Orange Data Mining or Python, develop both supervised and unsupervised basic machine learning models to address reaTMMI problems. Respond to the accompanying questions with thoughtful analysis. While collaboration with your group members is encouraged, you must independently design and implement your machine learning workflows and provide your answers.