Hey, what's up everyone?
My name is Luv Aggarwal, and I'm a Data Platform Solution engineer for IBM.
Machine Learning.
There's no doubt that this is an incredibly hot topic with significant interest from both business professionals as well as technologists.
So let's talk about what machine learning, or ML, is.
So, before we get too far into the details, I want to take a minute to talk about some terms that are often used interchangeably but have certain differences.
Terms like "artificial intelligence", "machine learning", and even "deep learning".
So, at the highest level, AI is defined as leveraging computers or machines to mimic the problem-solving and the decision-making capabilities of the human mind.
And machine learning is a subset within AI that's more focused on the use of various self-learning algorithms that derive knowledge from data in order to predict outcomes.
And then, finally, deep learning is a further subset within even machine learning, and deep learning is often thought of as scalable machine learning because it automates a lot of the feature extraction process away and eliminates the some of the human intervention involved to enable the use of some really, really big data sets.
