Deep-rooted deep learning

From beginner to intermediate
A lecture that covers the roots of artificial intelligence

It's not difficult if you know the basics 🎯

The world of deep learning is constantly evolving, and new models are constantly emerging. However, at the center of this change are core concepts that remain unchanged . This lecture explores those core concepts and provides the foundation necessary for a deep understanding of deep learning.

Through the lecture, implement the main models from the bottom up with clear explanations based on statistics! If you learn the main models thoroughly, you can easily implement and apply other models. New deep learning models are continuously coming out, but they are created by supplementing and applying existing models, so it is very important to properly understand the main models .

📖 To make learning easy and fun

Including implementation (practical project) in the lecture curriculum creates concerns for educators. Implementation requires various elements such as environment setting, debugging, and version management, but because of the effort put into the preliminary preparation process, you may not be able to focus on learning, and sometimes you may even give up the lecture in the middle.

To minimize these difficulties, all codes used in the class are provided through Colab , so you can take the class without any restrictions on environment settings as long as you have an Internet browser .

In addition, we provide various learning materials.

✅ Over 70 rich lecture slides cover the principles of the model in detail.
✅ Live coding allows you to understand the coding implementation process more deeply.
✅ We provide practice problems so that you can check your learning content on your own.

I hope that you will complete my lecture and become familiar with artificial intelligence. 💪

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After class

• You can properly understand the basic concepts of deep learning.

  • You can learn basic concepts through implementation by implementing the basic elements of deep learning, such as backpropagation and regularization, using only the numpy library without a platform such as Pytorch.

• You can fully understand major deep learning models such as CNN, RNN, Seq2Seq, Word Vector, and Transformer through conceptual depth and implementation from the ground up.

Features of this course

Things to note before taking the class