1 Machine Learning Algorithms
This chapter covers
- Types of ML algorithms
- Importance of learning algorithms from scratch
- Introduction to Bayesian Inference and Deep Learning
- Software implementation of machine learning algorithms from scratch
An algorithm is a sequence of steps required to achieve a particular task. An algorithm takes an input, performs a sequence of operations, and produces a desired output. The simplest example of an algorithm is sorting: given a list of integers, we perform a sequence of operations to produce a sorted list. A sorted list enables us to organize information better and find answers in our data.
Two popular questions to ask about an algorithm are how fast it runs (run-time complexity) and how much memory it takes (memory or space complexity) for an input of size n. For example, a comparison-based sort, as we’ll see later, has O(nlogn) run-time complexity and requires O(n) memory storage.