Please recommend some introductory tutorials on deep learning

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Please recommend some introductory tutorials on deep learning [Copy link]

 

Please recommend some introductory tutorials on deep learning

HUAHUAGONGZI

Here are some recommendations for introductory tutorials on deep learning:

1. Deep Learning Specialization by Andrew Ng (Coursera) : This is a series of courses offered by Professor Andrew Ng on Coursera that starts with the basics of deep learning and covers neural networks, convolutional neural networks, recurrent neural networks, and more.

2. Fast.ai Practical Deep Learning for Coders : Fast.ai provides practical deep learning courses for beginners, focusing on practice and projects, suitable for quickly getting started with deep learning.

3. CS231n Convolutional Neural Networks for Visual Recognition : Stanford University's CS231n course focuses on convolutional neural networks (CNNs) and is suitable for learners interested in image processing. It provides video lectures and course assignments.

4. Deep Learning Specialization by DeepLearning.AI (Coursera) : This is a deep learning specialization course provided by DeepLearning.AI. It starts with the basics of deep learning and gradually explains neural networks, convolutional neural networks, recurrent neural networks, etc.

5. PyTorch Tutorials : The PyTorch official website provides a wealth of tutorials and sample codes to help you quickly get started with the PyTorch deep learning framework.

These resources cover the basic knowledge and practical skills of deep learning, suitable for beginners to get started quickly. I wish you good luck in your study!

坎坎坷坷11

Here are some good resources for getting started with deep learning:

1. Coursera's Deep Learning Specialization :

   • The Deep Learning Special Course led by Professor Andrew Ng is a good choice for beginners. The course includes five courses, covering the basics of deep learning, neural networks, convolutional neural networks, recurrent neural networks, etc. Each course has theoretical explanations and practical projects, suitable for learners with zero foundation.

2. Dive into Deep Learning

   • This is an online deep learning textbook, co-authored by Li Mu, Aston Zhang and others. This textbook combines theory and practice, providing the basic knowledge and practical cases of deep learning. You can learn the basic concepts, common models and algorithms of deep learning through this textbook, and deepen your understanding through practical projects.

3. Stanford University's CS231n: Convolutional Neural Networks for Visual Recognition course :

   • CS231n is a classic course on convolutional neural networks, offered by the Computer Vision Research Group at Stanford University. This course covers the basics of deep learning, convolutional neural networks, recurrent neural networks, etc., and is suitable for learners who want to have a deeper understanding of deep learning.

4. PyTorch official tutorial :

   • The PyTorch official website provides detailed tutorials and sample codes, which are suitable for beginners to learn and refer to. You can learn the basic usage of PyTorch and the basics of deep learning through the PyTorch official tutorial, and you can also refer to the official documentation for more in-depth learning.

5. TensorFlow official tutorial :

   • The official TensorFlow website also provides a wealth of tutorials and documents, which are suitable for beginners to learn and refer to. You can learn the basic usage of TensorFlow and the basics of deep learning through the TensorFlow official tutorial, and you can also refer to the official documents for more in-depth learning.

The above are some teaching resources suitable for getting started with deep learning. You can choose the appropriate tutorial to learn according to your interests and needs. Through continuous learning and practice, you will be able to master the basic concepts and techniques of deep learning, laying a solid foundation for further in-depth learning and application.

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When you want to get started with deep learning, the following resources may be helpful to you:

1. Deep Learning Specialization on Coursera : A series of courses designed by Andrew Ng and other deep learning experts, including "Neural Networks and Deep Learning" and "Improving Deep Neural Networks: Hyperparameter Tuning, Regularization, and Optimization", which are suitable for beginners.

2. Udacity's Deep Learning Course : Provides courses covering deep learning basics, convolutional neural networks, recurrent neural networks, etc., including theoretical knowledge and practical projects.

3. Fast.ai : Offers free courses on deep learning with a focus on practice and applications, suitable for those who want to get started with deep learning quickly.

4. "Hands-On Deep Learning" : This is an open source textbook written by Li Mu, Aston Zhang and Zachary C. Lide. It explains the basic knowledge and practice of deep learning through the two frameworks of MXNet/Gluon and PyTorch.

5. TensorFlow and PyTorch official documentation : The official documentation provides a detailed introduction, tutorials, and sample codes for the deep learning framework, and is an important reference for learning deep learning.

No matter which resource you choose, make sure you understand what you learn and can practice and apply it in projects. Deep learning is a field that requires continuous practice and exploration. Only through continuous practice and project experience can you better master the relevant knowledge and skills. I wish you good luck in your studies!

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