Week 1: Delving into Machine Learning

Feb 25, 2019

Hello, my peers and other inquisitive persons,

I’ve spent the past week laying a solid foundation for my upcoming pursuits. From Dr. Andrew Ng’s Machine Learning course on Coursera to various research papers online, I’ve been studying a variety of important topics that will help me reach my final goal of predicting Obstructive Sleep Apnea using Machine Learning. These topics include, but aren’t limited to, Linear Regression, Logistic Regression, Probabilistic Graphical Models, and Pattern Recognition.

Working with a startup in this field has allowed me access to existing sleep data and I’ve started training an ML model for that data during this week. In addition, I’m just getting started on planning the logistics of an experiment where I’ll be collecting sleep data from volunteers and offering them a measurement of how likely they are to be diagnosed with Obstructive Sleep Apnea. While I want this to be a phenomenal learning experience, I also want to show people the importance of sleep health. (Yes, I know that sounds hypocritical to those that know me but I promise that I’ve made sleep a priority!)

I’ll be back soon with more updates!


2 Replies to “Week 1: Delving into Machine Learning”

  1. Nikhita J. says:

    Good job! The machine learning course you mentioned sounds good. I am planning to look into it and possibly take it.

  2. Sahil J. says:

    Awesome start! I certainly agree that sleep data analysis is an untapped well, and can’t wait to see what’s in store for week 2 & beyond. You could also try contacting medical facilities that are in this specialty right now, such that by the time your model is ready, you are able to test it (sorted out HIPPA-compliance issues, etc) on their data.

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