Description
Course info
Rating
(51)
Level
Beginner
Updated
Oct 25, 2017
Duration
2h 52m
Description

Play by Play is a series in which top technologists work through a problem in real time, unrehearsed, and unscripted. In this course, Play by Play: Machine Learning Exposed, James Weaver and Katharine Beaumont will start with the basics, and build up in an approachable way to some of the most interesting techniques machine learning has to offer. Explore Linear Regression, Neural Networks, clustering, and survey various machine learning APIs and platforms. By the end of this course, you'll get an overview of what you can achieve, as well as an intuition on the maths behind machine learning.

About the author
About the author

Katharine is a software developer, consultant and international conference speaker with a passion for learning: having degrees in Natural Sciences, a diploma Law and working to a Masters in Computer Science. She loves sharing knowledge, Machine Learning and cycling.

About the author

James Weaver is a Java developer, author, and speaker with a passion for cloud-native applications, machine learning, and quantum computing.

Section Introduction Transcripts
Section Introduction Transcripts

Course Overview
Welcome to this Play by Play with Pluralsight. This is an unscripted, unrehearsed discussion of machine learning with James Weaver and myself, Katharine Beaumont. We challenged ourselves to expose machine learning to you, what is it? What are the different types? Do you have to know calculus? And why is everyone talking about it at cocktail parties? In this play by play, we explore topics such as supervised learning, unsupervised learning, and reinforcement learning. We're going to give you some intuition on how some of the algorithms behind machine learning work. We'll look at linear regression, neural networks, blistering, and more. Don't know what that means? We'll explain. We're also going to show you some practical examples using APIs like deep learning for J and we'll point you in the direction of some exciting resources like Kaggle. So please join us on this journey, Exposing Machine Learning, so you can be the hit of your cocktail party circuit.