PyData SF 2016 Rohan Koodli | Machine Learning vs The Flu, Creating better Flu Vaccines with Python and Machine Learning
Millions of people are affected by the flu each year. I wanted to create a better way for scientists to make flu vaccines. My solution was to predict future flu genetic sequences so that scientists could easily analyze flu sequences and create vaccines. The main topics will include the use of Biopython and scikit-learn in a scientific environment, as well as data preprocessing and model selection.
Every year, millions of people are affected by the flu. Every year, we take a vaccine to possibly gain immunity from that year’s flu. However, the vaccines may not always work. In recent years, people have made attempts at predicting how the influenza virus has changed. For example, every year, world health officials try to predict what drugs to include in the coming year’s vaccine. However, many of the methods used have been called “questionable” by the National Institutes of Medicine. So, my goal in this project was to come up with a better way for scientists to make flu vaccines.
In my talk, I will show how I used Python to implement my flu prediction algorithm, as well as how I used libraries to make my algorithm more efficient and simpler in every step.