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AI is artificial intelligence, including machine learning. Machine learning is teaching computers how to learn from data and then make decisions, plans or guesses. Machine learning belongs to the cross-discipline of computer science and statistics, and it will appear with different appearance in many fields. For example, you should have heard these terms: data science, big data, artificial intelligence.

So what did AI learn? How to learn? Where do you start to learn?

This learning train of thought should be like this. Understand this field, enter the machine beginner stage, and then repeat the practice to enter the deep level of learning, repeat the practice and write the project to continue to learn, and then reach the stage of mastery. Therefore, if you want to understand the field of AI, the first thing is to set up a comprehensive view of the field of AI, cultivate a hobby of satisfaction, and then initially learn the basis of machine learning. After the foundation is laid, machine learning can be used to deal with a practical problem. After the actual combat experience has been accumulated, you can consider continuing to learn.

Basic knowledge required to enter the AI field: mathematics: linear algebra: matrix multiplication; higher numbers: derivation; probability theory: condition and posterior probability. English: online English dictionary, climbing the wall: you can Google anytime, anywhere, this is a very important thing.

Python programming in data Science

Practice the whole process of machine learning: collect data, preprocess and clean up data, set up models, practice and debug models, and comment on models.

In the end, set learning goals and deadlines for yourself and try your best to finish. We must lay a good foundation for learning, master the basic theory, and combine the practical theory, not only pay attention to one aspect. Try to write several algorithms from scratch. Be sure to think about the problem from multiple angles and think more about the value of each algorithm. Hang on, you're the next big god.

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