Launching into Machine Learning

First, we will give a brief history about machine learning. Next, we will discuss why neural networks are so efficient in solving many data science problems. Next, we'll discuss how to set up a supervised learning problem with gradient descent. We will discuss how to create datasets that allow generalization, and the best methods to do so in a repeatable way that allows experimentation.

Course Objectives: Learn why deep learning is so popular. Assess models using performance metrics and loss functions to identify common issues in machine learning. Make repeatable and scalable evaluation, testing, and training datasets