Description
The ultimate beginner’s guide to fuzzy logic in Python published by Udemy Academy. Understand 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 use in industrial equipment where the temperature can be adjusted automatically as the equipment heats or cools. Other examples of equipment are: vacuum cleaners (adjusting the suction power depending on the level and level of dirt), dishwashers and washing machines (adjusting the amount of water and soap used), digital cameras (autofocus adjustment), air. Air conditioning (temperature adjustment depending on the environment) and microwave (power adjustment depending on the type of food). In this course you will learn 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 the Python programming language! Below you can see the main content, divided into three parts:
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 the quality of the service) and calculating the suction power of a vacuum cleaner (based on the type of surface and the amount dirt).
Part 3: clustering with the fuzzy c-means algorithm. We classify a bank’s customers by credit card limit and statement total. 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. Ultimately, you will be able to create your own projects using fuzzy logic!
What you will learn in The Ultimate Beginner’s Guide to Fuzzy Logic in Python course:
- Understand 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.
- Implementing fuzzy systems using the skfuzzy library
- Simulate a fuzzy system to select the tip percentage to give in a restaurant.
- Fuzzy system simulation to adjust vacuum cleaner suction power based on surface type and amount of dirt
- Implementing data clustering using fuzzy c-means algorithm
Who should attend :
- Anyone interested in fuzzy logic.
- Students taking artificial intelligence or data science courses.
- Data scientists who want to deepen their knowledge of artificial intelligence algorithms.
Course Specifications
Course themes End of 2022/7
Course prerequisites
Basic Python Programming
Pictures
Introductory Video for the Ultimate Beginner’s Guide to Fuzzy Logic in Python
installation guide
After the clip, watch with your favorite reader.
english subtitles
Quality: 720p
Download link
password file(s): free download software
File size
1.01 GB