这四个主题有何不同？据我了解，他们从大量输入数据中学习并输出估计的输出。我的理解非常缺乏，因此我质疑这些。人们给出的例子，例如垃圾邮件、苹果橙猫狗识别、神经网络例子，对我来说毫无意义。
是否有一个更简单的示例可以更好地表示这四个主题，并通过编码来展示概念？我真的非常感激。
非常欢迎链接到您认为非常简单的代码示例。我需要一些相关的东西来更好地获得代码编写概念。
非常感谢!
最佳答案
Fuzzy logic is a form of many-valued logic in which the truth values of variables may be any real number between 0 and 1. By contrast, in Boolean logic, the truth values of variables may only be the integer values 0 or 1. Fuzzy logic has been employed to handle the concept of partial truth, where the truth value may range between completely true and completely false.1 Furthermore, when linguistic variables are used, these degrees may be managed by specific (membership) functions.
The field of AI research defines itself as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of success at some goal. Colloquially, the term "artificial intelligence" is applied when a machine mimics "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving" (known as Machine Learning).
汤姆·米切尔的机器学习:
A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E.
深度学习是利用深度神经网络进行机器学习。
因此:人工智能是机器学习的超集。机器学习是深度学习的超集。人工智能包括模糊逻辑:
资源
- Fuzzy logic lecture notes (德语)
- 电脑爱好者:Fuzzy logic
- IEEE:Fuzzy logic
- 汤姆·米切尔:Machine Learning
- 迈克尔·尼尔森:Deep Learning
关于machine-learning - 模糊逻辑、人工智能、机器学习、深度学习，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/43171325/