The Ultimate Beginners Guide to Fuzzy Logic in Python The Ultimate Beginners Guide to Fuzzy Logic in Python was published by Udemy Academy. Understand the fundamental theory and implement fuzzy systems with the skfuzzy library! Step-by-step implementations.
Fuzzy logic is a technique that can be used to model the human reasoning process in computers. It can be applied in several fields such as: industrial automation, medicine, marketing, home automation, etc.
A classic example is a use in industrial equipment where the temperature can be adjusted automatically as the equipment heats up or cools down. Other examples of equipment are vacuum cleaners (adjustment of suction power according to the level and level of dirt), dishwashers and washing machines (adjustment of the amount of water and soap used), digital cameras (adjustment of automatic focus), air.
Air conditioning (adjusting the temperature according to the environment) and microwave (adjusting the power according to the type of food). In this course, you will learn about the basic theory of fuzzy logic and mainly the implementation of simple fuzzy systems using the skfuzzy library. All implementations will be done step by step using Python programming language!
Part 1: Basic intuitions about fuzzy logic. You will learn about topics such as: linguistic variables, premises, result, membership functions, fuzzification and mathematical calculations for fuzzification.
Part 2: Implementation of fuzzy systems. You will run two examples: calculating the tips given in a restaurant (based on the quality of the food and quality of service) and calculating the suction power of a vacuum cleaner (based on the type of surface and amount of dirt).
Part 3: clustering with fuzzy c-means algorithm. We categorize a bank’s customers by credit card limit and total statement. You will understand how fuzzy logic can be applied in the field of machine learning.
All implementations are done step-by-step online using Google Colab, so you don’t have to worry about installing libraries on your device. In the end, you will be able to create your own projects using fuzzy logic!
What you will learn in The Ultimate Beginners Guide to Fuzzy Logic in Python course:
- Understanding the theoretical concepts of fuzzy logic such as: linguistic variables, premises, conclusion, membership, fuzzification and fuzzification
- Learn fuzzification calculations using the following methods: center, bisector, MOM, SOM, and LOM.
- Implementation of fuzzy systems using skfuzzy library
- Simulate a fuzzy system to select the tip percentage to be given in a restaurant.
- Fuzzy system simulation to adjust the suction power of the vacuum cleaner according to the type of surface and the amount of dirt
- Implementation of data clustering using fuzzy c-means algorithm
Who is this course suitable for:
- Anyone interested in fuzzy logic.
- Students who are taking artificial intelligence or data science courses.
- Data scientists who want to increase their knowledge in artificial intelligence algorithms.
- Publisher: Udemy
- Instructor: Jones Granatyr , IA Expert Academy , Eduardo Alexandre Franciscon
- English language
- Education level: introductory
- Number of courses: 33
- Training duration: 4 hours and 8 minutes
Fuzzy Logic in Python Course headings at the end of 2022/7
Fuzzy Logic in Python Course prerequisites
Basic Python programming
Fuzzy Logic in Python Pictures
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