How is statistics related to machine learning?
Machine learning and statistics are closely related fields in terms of methods, but distinct in their principal goal: statistics draws population inferences from a sample, while machine learning finds generalizable predictive patterns.
How is machine learning related to computer science?
Computer scientists invented the name machine learning, and it’s part of computer science, so in that sense it’s 100\% computer science. But the content of machine learning is making predictions from data. It is more that computer scientists and statisticians view “making predictions from data” through different lenses.
What is the theory of machine learning?
The bulk of the “theory” one encounters in machine learning is related to machine learning algorithms. If you ask any beginner about why they are frustrated with the theory, you will learn that it is in relation to learning how to understand or use a specific machine learning algorithm.
What are the prerequisites to learn machine learning as a developer?
This is crap if you are a developer who is primarily interested in using machine learning as a tool to solve problems rather than being a researcher in the field. The traditional approach requires that you learn all of the prerequisite mathematics like linear algebra, probability and statistics before learning the theory of algorithms.
Is machine learning just for the mathematical elite?
Machine learning is not just for the mathematical elite. You can learn how machine learning algorithms work and how to get the most from them without diving deep into multivariate statistics. You do not need to be good at math.
How does the system learn to perform the task T?
In order to perform the task T, the system learns from the data-set provided. A data-set is a collection of many examples. An example is a collection of features. Machine Learning is generally categorized into three types: Supervised Learning, Unsupervised Learning, Reinforcement learning