I want to get started with machine learning from scratch, what should I do?

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I want to get started with machine learning from scratch, what should I do? [Copy link]

 

I want to get started with machine learning from scratch, what should I do?

Howard_Sun

For those who are new to machine learning from scratch, the following steps can help you build a foundation and gradually deepen your learning:

1. Learn the basic concepts :

   • Start learning the basic concepts of machine learning, including supervised learning, unsupervised learning, semi-supervised learning, reinforcement learning, etc. Understand the definitions and basic principles of these concepts.

2. Master the basics of mathematics :

   • Learn the necessary mathematical knowledge, including linear algebra, probability statistics, calculus, etc. These mathematical knowledge are the basis for understanding machine learning algorithms and methods.

3. Learn the basics of programming :

   • Learn a programming language, such as Python, as your tool for learning machine learning. Master basic programming concepts and syntax, as well as how to use programming languages for data processing and analysis.

4. Online courses and teaching materials :

   • Look for some high-quality online courses and teaching materials, such as machine learning courses on platforms such as Coursera, edX, and Udacity. These courses usually include video lectures, practical projects, and online forums, which can help you learn machine learning knowledge systematically.

5. Exercises :

   • During the learning process, try to do some simple machine learning projects. These projects can be tasks on public data sets, such as house price prediction, image classification, etc. Through practical project exercises, you can deepen your understanding of machine learning algorithms and methods.

6. Get involved in the community :

   • Join some machine learning communities or forums, such as GitHub, Stack Overflow, etc. In these communities, you can ask questions to others, participate in discussions, and share experiences and resources with other learners.

7. Continuous Learning :

   • Machine learning is a field that is constantly evolving and progressing, and requires continuous learning and practice. Keep reading the latest research papers, attending relevant seminars and conferences, and keep up with the field of machine learning.

By following the above steps, you can gradually build the foundation of machine learning and continuously improve your abilities in practice. I wish you good luck in your studies!

行走的风

For beginners who want to learn machine learning, here are some steps and suggestions:

1. Understand the basic concepts: Before you start learning machine learning, you should first understand some basic concepts, such as what is machine learning, supervised learning, and unsupervised learning.

2. Learn the basics of mathematics: Machine learning involves some mathematical knowledge, including linear algebra, probability statistics, and calculus. You can learn this mathematical knowledge through online courses, textbooks, or video tutorials.

3. Master programming skills: Python is a common programming language for machine learning, so it is recommended that you learn the Python programming language. You can learn the basics of Python through online tutorials, books, or video courses.

4. Learn machine learning algorithms: Learn some basic machine learning algorithms, such as linear regression, logistic regression, decision tree, etc. You can learn the principles and implementation of these algorithms through online courses, textbooks or open courses.

5. Practical projects: Completing some machine learning projects is an important way to learn. You can start with some simple projects, such as predicting house prices, classifying handwritten numbers, etc. In the process of practice, you will learn a lot of knowledge and skills.

6. Participate in online courses and communities: Participating in some high-quality online courses and machine learning communities can accelerate your learning progress and gain more learning resources and communication opportunities.

7. Continuous learning and practice: Machine learning is an evolving field and you need to continue learning and practicing to keep up with the latest technology and research advances.

By following the above steps, you can gradually build up a basic understanding and skills in machine learning and continue to improve your level. I wish you good luck in your studies!

liliukan

For electronic engineers who are new to machine learning, here are some recommended steps:

1. Learn basic mathematics and programming knowledge: Before starting to learn machine learning, it is recommended to learn basic mathematics knowledge, including linear algebra, probability statistics, and calculus. At the same time, learn a programming language, such as Python, because Python is widely used in the field of machine learning.

2. Master Python programming: Python is one of the most commonly used programming languages in the field of machine learning, so you need to master Python's basic syntax and common libraries such as NumPy, Pandas, and Matplotlib.

3. Learn the basics of machine learning: Understand the basic concepts and common algorithms of machine learning, such as supervised learning, unsupervised learning, regression, classification, clustering, etc. You can learn this knowledge through online courses, textbooks, or online resources.

4. Participate in online courses or tutorials: Participate in some online courses or tutorials for beginners, such as Andrew Ng's "Machine Learning" course on Coursera, Andrew Ng's "Deep Learning Specialization Course", etc. These courses usually start from the basics and gradually introduce the concepts and algorithms of machine learning.

5. Read relevant books and textbooks: You can read some classic machine learning books, such as "Statistical Learning Methods" and "Practical Machine Learning". These books will explain the principles and applications of machine learning in depth and provide some practical cases.

6. Practical projects: Use practical projects to consolidate what you have learned. You can choose some simple machine learning projects, such as house price prediction, handwritten number recognition, etc., and try to implement them in Python. Practical projects can deepen your understanding of machine learning algorithms and tools.

7. Participate in communities and discussions: Participate in machine learning communities and forums to communicate and discuss with other learners. You can join some online communities for machine learning, such as Kaggle, GitHub, etc., to learn and share experiences with other practitioners.

8. Continuous learning and practice: Machine learning is an evolving field that requires continuous learning and practice. Stay curious about new methods and techniques and keep improving your skills.

By following the above steps, you can get started with machine learning from scratch and gradually master its basic concepts and skills. I wish you good luck in your studies!