How to start learning deep learning, what are the recommended learning paths and resources?

Learning deep learning is an exciting and challenging task. The following is a recommended learning path and resources to help you get started with deep learning:

1. Mathematical and statistical foundations: Deep learning involves many mathematical concepts, including linear algebra, calculus, probability theory, and statistics. Make sure you have some familiarity with these basics.

2. Python programming language: Python is the main programming language for deep learning, and it is supported by a wealth of libraries and tools. Learning Python is the foundation of deep learning.

3. Machine Learning Basics: Before going deep into deep learning, it is recommended to master some basic concepts and algorithms of machine learning, such as supervised learning, unsupervised learning, and reinforcement learning.

4. Recommended study resources:

   • "Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville. This book is a classic textbook in the field of deep learning, covering the basic theory and practice of deep learning.
   • Andrew Ng's Deep Learning Specialization on Coursera. This is an excellent online course that covers many aspects of deep learning and is taught by experts in the field of deep learning.
   • The fast.ai website offers a free deep learning course for beginners to get started.
   • Online learning platforms such as Udacity and edX also have many in-depth learning courses, and you can choose the right course according to your interests and needs.

     

5. Using Deep Learning Frameworks: Learn and use one or more popular deep learning frameworks such as TensorFlow, PyTorch, and more. These frameworks provide powerful tools and libraries for implementing deep learning models.

6. Practical Projects: Consolidate what you have learned through practical projects. Try to solve some deep learning related problems, participate in Kaggle competitions, or implement some classic deep learning models.

7. Read research papers and blogs: Follow the latest research in the field of deep learning, read papers and technical blogs, and learn about the latest trends and innovations in the industry.

8. Join communities and forums: Join deep learning-related communities and forums, such as relevant sections on GitHub, Stack Overflow, and Reddit, to communicate and share experiences with other learners and professionals.

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Learning deep learning takes time and persistence, but once you develop a solid foundation and gain enough hands-on experience, you'll be able to succeed in this exciting field. Good luck!