Learn the basic concepts of Machine Learning with the power of Python 3.8
What you’ll learn
- The basic concepts of Machine Learning
- The Machine Learning Models
- How to use Machine Learning in your own Projects
- Improved understanding of the Python language
Who is this course for?
– This course is for anyone who wants to learn about the basic concepts and models of Machine Learning. It is highly recommended that you also have a solid foundation and undertsanding of how Python works. We will be using Python 3.8 for all the examples.
What is Machine Learning? (Wikipedia)
– Machine learning (ML) is the study of computer algorithms that improve automatically through experience and by the use of data. It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as “training data”, in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as in medicine, email filtering, speech recognition, and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.
What is Python? (Wikipedia)
– Python is an interpreted high-level general-purpose programming language. Python’s design philosophy emphasizes code readability with its notable use of significant indentation. Its language constructs as well as its object-oriented approach aim to help programmers write clear, logical code for small and large-scale projects.
Python is dynamically-typed and garbage-collected. It supports multiple programming paradigms, including structured (particularly, procedural), object-oriented and functional programming. Python is often described as a “batteries included” language due to its comprehensive standard library.