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How to Learn Machine Learning
To learn machine learning, we need to understand the basic concepts and ideas behind it. We have to build up our knowledge by studying mathematics and computer science, ideally starting from first principles. Once you get a solid grounding in these subjects, you are ready for practical applications of machine learning.
Then you must be able to apply the concepts and ideas behind machine learning. You need to write code, understand programming languages like python, C++ or Java. Then you need a software framework that can do all of this for you so that your time is spent writing program logic rather than low level coding.
Learning machine learning means, in practice, creating a classifier. We create a classifier that can take an input and output an answer based on this input. The ideal situation would be to have the computer program learn from examples of correct answers so that it can do everything by itself.
If you want to learn machine learning, I would recommend that you read the book 'Artificial Intelligence: A Modern Approach' by Stuart Russel and Peter Norvig. This is widely considered to be one of the best books on AI in general.
Machine learning is also based on statistics. Therefore, it would be very useful to have a good grounding in statistical concepts.
Machine learning is related to artificial intelligence. With machine learning, we create a computer program that can do tasks for us.