Soft Computing and Machine Learning are related fields, but they are not the same thing. Soft Computing is a subfield of Artificial Intelligence that deals with the development of algorithms and techniques that can handle uncertainty, imprecision, and partial truth. It includes techniques such as fuzzy logic, neural networks, and genetic algorithms.

On the other hand, Machine Learning is a subfield of Artificial Intelligence that focuses on the development of algorithms that can learn from data and make predictions or decisions based on that learning. It includes techniques such as supervised learning, unsupervised learning, and reinforcement learning.

So, while Soft Computing is concerned with handling uncertainty and imprecision, Machine Learning is concerned with learning from data. However, there is some overlap between the two fields, and some techniques from Soft Computing, such as neural networks, are commonly used in Machine Learning.
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