Introduction to Machine Learning
Machine learning, is essentially a way for implementing artificial intelligence.
A kind of sub-group of AI that focuses on the ability of machines to receive a set of data and learn on their own, modifying algorithms as they receive more information about what they are processing.
Very often, the terms AI and machine learning (ML) have been used interchangeably, especially in the realm of big data.
The term “machine learning” was coined after AI, understood as: “the ability of a machine to learn without being explicitly programmed”. Machine learning is thus a way of “educating” an algorithm so that it can learn from various environmental situations.
Education, or even better training, involves the use of huge amounts of data and an efficient algorithm in order to adapt (and improve) according to the situations that occur.
The primary techniques used in machine learning: supervised learning, unsupervised learning, semi-supervised learning and reinforcement learning will be presented.
Moreover, some examples of machine learning application in everyday life will be shown, coupled with the description of jobs and skills related to this technology.
Course Includes
- 8 Modules
- 5 Topics
- 1 Quiz
- Course Certificate
