Using Machine Learning Autoencoders Neural Networks for Dimensional Reduction of Genomic Datasets
“Machine learning is a well-known field in today’s society when it comes to technology. The first thing that probably comes to your mind is AI, which is a fair assumption, and I do have to admit, yes, machine learning and AI are related in some ways. But this is not involved with robotics similar to what you see in movies or science fairs, or robotics classes. It’s done more so in programming and is ever more present in the world of coding and software engineering. If you had a noisy image, a machine could make it less noisy on the image! If you had a file that was quite big in data size and you wanted to compress it down, a machine could do that! But what if I told you, you could condense down large dataset files, and the files took up so much of your storage on a small thumb drive, and it took forever for a machine to learn and output results? Well, now you can! This is how we use a neural network called an autoencoder and use the dimensionality reduction method to condense our data in Genomics!”
SFTE 445 – Introduction to Machine Learning and AI
Dr. Ernest Bonat
4pm – L204