Introduction to Machine Learning

Description
This video will give a general introduction to intelligent systems and show specific examples in computer alogrithms. He uses the first part of the video to demonstrate exactly what a machine learning programme does and what structures it needs to work. The key fundamentals of machine learning are clearly outlined using this analogy, giving you a basic grasp of their function.

David then goes on to discuss vectors and how all data can be representable as vectors. He then simplifies the process of data and vector mapping through the use of his cat and dog analogy. This makes the whole process simple to understand for beginners to machine learning. He shows how data regarding cats and dogs (eg. their weight and height) can be inputted as vectors, which when inputted into the machine learning software, will be able to establish whether each vector represents a cat or a dog.

David shows how software can begin to learn from the data and establish trends and patterns in the data that can be used to determine the species. This video will show how machine learning works by pulling out the structure from the data and using it to identify and classify different things.

David then discusses the different kinds of machine learning algorithms and their applications. These are supervised learning, unsupervised learning and reinforcement learning. He apprpaches each of these types of machine learning and analyses exactly how they work and how they can be used in everyday life.

This video is an essential tool for anyone wanting to get involved in the field of machine learning, no matter their experience.

18 mins 52