Welcome to Morris Lee A.I.

Hi! I'm Morris Lee. I work in a number of Artificial Intelligence areas, but primarily in machine learning and deep learning areas. I am part of the MSc Data Science program at USM. Here are my deployed machine learning models using flask and Heroku. For more about my portfolios, please visit my Portfolio website and my GitHub.

Email me at info.leekahwin@gmail.com

(1) Cat identifier using Deep Learning

Test with your own image to know whether the image is a Cat or not

(2) Titanic Survival Prediction

Ticket Class :	First Class Second Class Third Class
Gender :	Male Female
Age:
# of siblings / spouses on the Titanic:	0 1 2 3 4 5 >=6
# of parents / children on the Titanic	0 1 2 3 4 5 >=6
Passenger fare $(0~500):
Port of Embarkation:	Cherbourg Queenstown Southampton

(3) Parkinson's Disease Prediction

Using voice measures collected from telemonitoring method allow participants to identify their Parkinson's Disease Rating Scale remotely

Age:
Sex:	Male Female
Voice Measure - Jitter(%)	(lower & upper boundary: -0.0012, 0.0116)
Voice Measure - Shimmer.APQ11	(lower & upper boundary: -0.0099, 0.0583)
Voice Measure - NHR	(lower & upper boundary: -0.0200, 0.0625)
Voice Measure - HNR	(lower & upper boundary: 11.8490, 32.0010)
Voice Measure - RPDE	(lower & upper boundary: 0.2534, 0.8304)
Voice Measure - DFA	(lower & upper boundary: 0.4234, 0.8841)
Voice Measure - PPE	(lower & upper boundary: -0.0059, 0.4267)