Please recommend some introductory tutorials on convolutional neural networks

明月昊天

Please recommend some introductory tutorials on convolutional neural networks [Copy link]

 

Please recommend some introductory tutorials on convolutional neural networks

李雪丽

Here are some introductory resources for teaching Convolutional Neural Networks (CNN):

1. Getting Started with Convolutional Neural Networks (CNN) : You can find some getting started guides and tutorials online. These resources usually introduce the basic concepts, structure, and principles of CNN, and demonstrate how to use CNN for tasks such as image classification and object detection through sample code.

2. Deep learning courses : Many deep learning courses involve convolutional neural networks, such as Andrew Ng's "Deep Learning Professional" course, Li Hongyi's deep learning course, etc. These courses usually introduce the principles and applications of CNN in detail and provide practical projects for learners to practice.

3. Deep learning framework documentation : Deep learning frameworks such as TensorFlow, PyTorch, and Keras all provide detailed documentation and tutorials, including guides and sample code for using CNN. You can refer to the documentation of the corresponding framework to learn how to use CNN.

4. Blog articles and forum discussions : There are many blog articles and forums discussing topics about CNN on the Internet. You can learn and exchange knowledge and experience about CNN by reading these articles and participating in discussions.

5. Deep learning community : Join some deep learning communities, such as GitHub, Stack Overflow, Reddit, etc., follow CNN-related projects and topics, exchange experiences and solve problems with other learners and professionals.

6. Practical Projects : One of the most effective ways to learn CNN is through practical projects. You can choose some classic CNN projects, such as image classification, object detection, semantic segmentation, etc., and improve your skills by implementing and debugging models.

I hope the above resources can help you quickly get started with convolutional neural networks. Good luck with your studies!

钱小公主

Here are some great resources for getting started with Convolutional Neural Networks (CNN):

1. Stanford CS231n: Convolutional Neural Networks for Visual Recognition :

   • This is an open course at Stanford University, taught by Professor Fei-Fei Li. The course covers the application of convolutional neural networks (CNN) in the field of image recognition, including the basic principles of CNN, network structure, training techniques, etc. The course is taught in a combination of theory and practice, suitable for people who want to learn CNN in depth.

2. Deep Learning Specialization (Coursera) :

   • This is a series of courses taught by Professor Andrew Ng of Stanford University, which covers the content of convolutional neural networks. In particular, the fourth course "Convolutional Neural Networks" specifically explains the principles, applications and training methods of CNN. The course focuses on practice and project application, and is suitable for learners who want to quickly get started with CNN.

3. Deep Learning with Python (by Franois Chollet) :

   • This book is written by Fran?ois Chollet, one of the founders of Keras. It introduces how to build deep learning models using Python and Keras. The book contains many chapters on CNN, covering the basics, applications, and practical techniques of CNN. It is suitable for readers who want to learn CNN through practical projects.

4. PyTorch official tutorial :

   • PyTorch provides a wealth of tutorials and documentation to help you quickly get started with deep learning and the PyTorch framework. The PyTorch official tutorial includes tutorials and sample codes on CNN, which can help you understand how to build and train CNN models using PyTorch.

These teaching resources are a good choice for getting started with learning convolutional neural networks, covering all aspects from theory to practice, and are suitable for learners of different levels and interests.

mtgdyc

For electronic engineers looking to get started with convolutional neural networks (CNNs), here are some recommended resources:

1. Deep Learning for Beginners : This tutorial covers the basic concepts and principles of convolutional neural networks and is suitable for beginners to get started quickly. Here you can learn the basic knowledge of CNN, such as the basic structure, convolutional layer, pooling layer, etc.

2. Tutorial videos on YouTube : There are many tutorial videos on convolutional neural networks on YouTube, such as 3Blue1Brown's neural network series, sentdex's Python deep learning series, etc. These videos can help you quickly understand the basic principles and applications of CNN.

3. Coursera courses : Coursera provides some deep learning courses offered by well-known universities and institutions, including relevant content about CNN. You can choose the course that meets your needs to study.

4. Kaggle Kernels : Kaggle provides many projects and competitions based on convolutional neural networks. You can find various practical projects here and learn other people's codes and techniques.

5. fast.ai : fast.ai offers a free deep learning course that covers CNNs. Their course combines hands-on projects with theory, making it perfect for those who want to get started quickly.

These are some resources for electronic engineers to get started with convolutional neural networks. I hope they are helpful to you!

fjdeepblue

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