At a Glance

Name: Parkinson Detection From Voice Data (Part1 iBest Workshop)
Price: Free CAD
Rating: 4.8 (87 reviews)
Author: joseph_santarcangelo, sina_nazeri, alice_rueda

This Guided Project will provide an introduction to Artificial Intelligence and Machine Learning using Python and Scikit-Learn. Through it, learners will learn how to use Python and Scikit-Learn to build a Machine Learning model to accurately detect Parkinson’s Disease from voice patterns. By the end of this project, you will have gained the skills needed to start building your own AI-powered predictions.

This project aims to leverage machine learning techniques to analyze voice recordings and detect the presence of Parkinson's disease, a neurological disorder that affects movement. The goal is to develop a model that can accurately predict the disease using voice data, which could help in the early detection and treatment of the condition.

To achieve this objective, the project will involve the use of Python for data analysis and machine learning. Machine learning algorithms such as decision trees and support vector machines will be implemented to analyze voice features and make predictions about the presence of Parkinson's disease. The model will be evaluated for performance metrics.

In addition to implementing machine learning algorithms, the project will also involve conducting a grid search for tuning the parameters of the model. This step is essential for optimizing the performance of the model and improving its predictive power. Visualizing the decision tree model will also be part of the project, which can help in interpreting the results and identifying important features.

A Look at the Project Ahead

objectives for the project "Using Machine Learning to Analyze Voice Disorders for Parkinson's Disease Detection":

Develop a machine learning model that can accurately predict the presence of Parkinson's disease based on voice recordings.
Implement different machine learning algorithms such as decision trees and support vector machines to analyze voice features and make predictions.
Conduct a grid search to optimize the parameters of the model and improve its predictive power.
Visualize the decision tree model to aid in interpreting the results and identifying important features.

What You'll Need

Your enthusiasm and a browser. This project runs on IBM skills' network cloud, and there is no need for any local installation.

Offered By: IBMSkillsNetwork

Parkinson Detection From Voice Data (Part1 iBest Workshop)

At a Glance

A Look at the Project Ahead

What You'll Need

This Guided Project is part of the following Learning Paths