Intro to Machine Learning on the cheap and without a PhD in math: Overview
Presented by: Jim Wilson
Machine learning has traditionally required a command of advanced mathematics, years of university training, and expensive hardware to implement. Now with better open source tools and online resources it’s easier than ever to create your own robust neural networks. Be it image recognition, natural language processing, or sophisticated data categorization, it’s possible to learn the fundamentals of machine learning and experiment with different architectures to create your own individually optimized solutions.
This talk will cover the basics of neural nets and how to use Google Colab notebooks, Python, and the fastai/PyTorch libraries to develop your own customized neural networks…all for free.