How to learn machine learning from scratch

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How to learn machine learning from scratch

WANG_2023

Even if you have no basic knowledge of machine learning, you can get started by following these steps:

1. Build a mathematical foundation :

   • Start learning the basics of mathematics, especially those related to machine learning, including linear algebra, probability theory, and statistics. This knowledge is the basis for understanding machine learning algorithms and techniques. You can learn this mathematics through free online courses, textbooks, or video tutorials.

2. Learn programming skills :

   • Choose a programming language and start learning it. Python is one of the most commonly used programming languages in the field of machine learning, so it is recommended that you learn Python programming. You can learn the basics of Python and programming skills through online tutorials, books, or video courses.

3. Learn the basics of machine learning :

   • Understand the basic concepts, algorithms, and techniques of machine learning. You can learn the basics of machine learning, including supervised learning, unsupervised learning, model evaluation, etc., through free online courses, textbooks, or online video courses.

4. Practical projects :

   • Practice is the key to learning machine learning. Through practical projects, you can consolidate your knowledge and improve your skills. You can choose some simple projects to start, such as classification or regression analysis using public datasets. As your skills gradually improve, you can try more complex projects and apply machine learning techniques to solve real-world problems.

5. Continuous learning and improvement :

   • Machine learning is a rapidly evolving field, and you need to maintain a continuous learning attitude and constantly update your knowledge and skills. You can continuously improve your skills by taking online courses, reading academic papers, and participating in open source projects.

Through the above steps, you can learn machine learning from scratch and gradually master the relevant theories and techniques. It is important to maintain patience and a continuous learning attitude, and constantly accumulate experience in practice to become an excellent machine learning practitioner.

xiao0409

You may already have some basic knowledge of programming and mathematics, which will provide you with a good starting point for learning machine learning. Here are some ways you can get started with machine learning from scratch:

1. Learn basic math knowledge : Machine learning involves many math concepts, including linear algebra, probability statistics, calculus, etc. You can lay a solid math foundation for subsequent machine learning by reviewing and deepening your understanding of these math knowledge.

2. Learn programming basics : Most machine learning algorithms are implemented through programming, so you need to have a certain programming foundation. Python is one of the most commonly used programming languages in the field of machine learning. You can prepare for subsequent machine learning by learning Python programming basics.

3. Learn the basics of machine learning : Once you have mastered the basics of mathematics and programming, you can start learning the basics of machine learning. You can learn the basic theories, common algorithms, and practical methods of machine learning by reading classic machine learning textbooks, taking online courses, or watching related videos.

4. Practical projects : The purpose of learning theoretical knowledge is to apply it to practical projects. Once you have mastered the basic knowledge of machine learning, you can start doing some practical projects. You can start with simple projects, such as using classic datasets for classification or regression tasks, and gradually increase the difficulty to explore more complex machine learning algorithms and application scenarios.

5. Participate in communities and discussions : Join machine learning related communities and forums, exchange experiences and learning experiences with other learners, and ask questions to experienced people. This will help deepen your understanding of machine learning and improve your learning efficiency.

6. Continuous learning and practice : Machine learning is a field that is constantly developing and evolving, and you need to keep learning new knowledge and techniques. You can keep paying attention to and learning about the field of machine learning by reading academic papers, attending academic conferences, and participating in open source projects.

In general, you already have some of the basics needed to learn machine learning. Through continuous learning and practice, I believe you will quickly master the relevant knowledge and skills of machine learning.

JEREMY123

As an electronics engineer, you may have some knowledge of programming and mathematics, but you may have no experience with machine learning. Here are the steps you can take to get started with machine learning:

1. Learn basic math knowledge : Machine learning involves many mathematical concepts, including linear algebra, probability statistics, calculus, etc. You can learn these basic math knowledge by self-study or by taking relevant online courses to lay a solid mathematical foundation for subsequent machine learning.

2. Learn programming basics : Most machine learning algorithms are implemented through programming, so you need to have a certain programming foundation. Python is one of the most commonly used programming languages in the field of machine learning. You can learn Python programming basics by self-study or taking online courses.

3. Learn the basics of machine learning : Once you have mastered the basics of mathematics and programming, you can start learning the basics of machine learning. You can learn the basic theories, common algorithms, and practical methods of machine learning by reading classic machine learning textbooks, taking online courses, or watching related videos.

4. Practical projects : The purpose of learning theoretical knowledge is to apply it to practical projects. Once you have mastered the basic knowledge of machine learning, you can start doing some practical projects. You can start with simple projects, such as using classic datasets for classification or regression tasks, and gradually increase the difficulty to explore more complex machine learning algorithms and application scenarios.

5. Continuous learning and practice : Machine learning is a field that is constantly developing and evolving, and you need to keep learning new knowledge and techniques. You can keep paying attention to and learning about the field of machine learning by reading academic papers, attending academic conferences, and participating in open source projects.

In general, getting started with machine learning from scratch requires systematic learning and continuous practice to improve your abilities. With unremitting learning and practice, I believe you will make good progress in the field of machine learning.