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

guqian999

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

 

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

轻舟已过万重山

To get started with deep learning, you can follow these steps:

1. Master basic mathematics and programming knowledge: Deep learning involves many mathematical concepts, such as linear algebra, calculus, and probability statistics, so it is recommended to learn these basic mathematical knowledge first. At the same time, mastering a programming language, such as Python, and related scientific computing libraries, such as NumPy and Pandas, is the basis for deep learning.

2. Learn the basic theory of deep learning: Understand the basic principles, common models and algorithms of deep learning. You can learn through online courses, textbooks or academic papers. Focus on mastering the structure of neural networks, back propagation algorithms and common deep learning frameworks.

3. Complete online courses or tutorials: Choose some high-quality online courses or tutorials to learn deep learning. For example, there are many deep learning-related courses on platforms such as Coursera, Udacity, and edX, such as Andrew Ng's "Deep Learning Specialization Course" and Fast.ai's "Practical Deep Learning for Coders".

4. Practical projects: Improve your practical skills by completing some deep learning projects. You can start with simple projects such as image classification and text classification, and gradually expand to more complex projects such as object detection and speech recognition. At the same time, try to explore different deep learning models and technologies in practice.

5. Read papers and books: Read classic papers and authoritative books in the field of deep learning to learn about the latest research progress and technology trends. You can pay attention to some well-known deep learning conferences and journals, such as NeurIPS, ICML, and IEEE Transactions on Pattern Analysis and Machine Intelligence.

6. Participate in communities and discussions: Join deep learning-related communities and forums to exchange experiences and ideas with other learners and experts. You can participate in online forums such as r/MachineLearning on Reddit and deep learning projects on GitHub to share learning experiences and solve problems with others.

7. Continuous learning and practice: Deep learning is a rapidly evolving field that requires continuous learning and practice to keep up with the latest advances. Maintaining a continuous learning attitude and constantly trying new ideas and techniques will help improve your deep learning ability.

In short, getting started with deep learning requires mastering the basics step by step, and improving your skills through practical projects and continuous learning. At the same time, it is also important to communicate and share experiences with others, which can accelerate learning progress and broaden your horizons.

zhanggl

If you want to start learning deep learning from scratch, here are some steps and suggestions:

1. Build a mathematical foundation :

   • Deep learning involves many mathematical concepts, including linear algebra, calculus, probability theory, statistics, etc. It is recommended to learn these basic mathematical knowledge first, especially linear algebra and calculus, because they are the core of deep learning.

2. Learn the basics of programming :

   • Master a programming language, such as Python, which is one of the most commonly used programming languages in the field of deep learning. Learn Python's basic syntax and programming skills, including variables, data types, control flow, functions, etc.

3. Learn the basics of machine learning :

   • Before learning deep learning, it is recommended to understand the basic concepts and algorithms of machine learning, such as supervised learning, unsupervised learning, regression, classification, clustering, etc. This will lay the foundation for your subsequent learning of deep learning.

4. Learn the basics of deep learning :

   • Learn the basics of deep learning, including neural network structure, forward propagation, back propagation, loss function, optimization algorithm, etc. You can learn through online courses, textbooks, video tutorials and other resources.

5. Choose the right learning resources :

   • Choose learning resources that suit you, such as online courses (such as Coursera, Udacity, edX, etc.), textbooks (such as "Deep Learning", "Neural Networks and Deep Learning", etc.), blogs, video tutorials, etc.

6. Hands-on projects :

   • Reinforce your knowledge through hands-on projects. Start with simple deep learning projects, such as image classification, text classification, house price prediction, etc. Gradually increase the complexity and difficulty of the projects.

7. Participate in practical projects :

   • Join a community or forum for deep learning enthusiasts to exchange learning experiences and project results with others, and get more learning resources and technical support. Asking questions and answering others' questions in practical projects is also part of learning.

8. Continuous learning and practice :

   • Deep learning is a rapidly developing field, and continuous learning of new knowledge and techniques is essential. Improve your skills by constantly practicing projects and trying new applications.

The above are the general steps and suggestions for learning deep learning from scratch. I hope it will be helpful to you!

shengju

As an electronic engineer, if you want to learn deep learning from scratch, here are some steps and suggestions:

1. Understand basic concepts: Before you begin, understand the basic concepts and principles of deep learning, including neural networks, forward propagation, back propagation, gradient descent, etc. These are the basics of deep learning, and understanding them will help you better learn and apply deep learning techniques.

2. Learn mathematics and statistics: Deep learning involves a lot of mathematics and statistics, including linear algebra, calculus, probability theory, etc. You can learn this knowledge through online courses, textbooks or self-study to lay a solid mathematical foundation for subsequent deep learning.

3. Choose learning resources: Find deep learning learning resources that are suitable for you, such as online courses, textbooks, video tutorials, etc. Some well-known deep learning textbooks and courses such as "Deep Learning" (written by Ian Goodfellow, etc.) and deep learning special courses on Coursera are good choices.

4. Learn programming languages and tools: Deep learning is usually implemented using programming languages such as Python and tool libraries such as TensorFlow, PyTorch, etc. You can start your deep learning journey by learning the Python programming language and the corresponding deep learning tool libraries.

5. Complete tutorials and projects: Practice your deep learning knowledge by completing some online tutorials and projects. You can start with some simple projects and gradually increase the difficulty to deepen your understanding of deep learning principles and applications.

6. Participate in practical projects and competitions: Join some deep learning projects or competitions to collaborate or compete with others to solve some practical problems together, which can accelerate your learning and improve your skills.

7. Continuous learning and practice: Deep learning is a rapidly developing field that requires continuous learning and practice to keep up with the pace of development. Stay curious, pay attention to the latest research results and technological advances, and constantly improve your skills.

Through the above steps, you can learn deep learning from scratch and gradually master its basic principles and application skills. With continuous learning and practice, you will gradually become an expert in the field of deep learning.

fjdeepblue

Very good information, the summary is very detailed and valuable for reference, thank you for sharing