Using Keras as the front-end and TensorFlow as the back-end, you will learn from the basic theory of deep learning programming to simple examples, and apply deep learning to real-world tasks. We have planned to help you do so. You can find examples of areas where deep learning is mainly applied , such as the creation of various prediction programs, the creation of recognition-identification programs, sentence similarity identification programs, and the creation of adversarial generative neural network programs, on the web or in books. It includes not only representative examples that can be applied in practice, but also basic examples and various theoretical explanations for each. It would be helpful to listen to the lecture while downloading and executing the examples linked to each chapter. Since each lecture is about 20 minutes long and each theoretical explanation is divided into lectures, I think you will understand all the theoretical parts if you listen to the lectures until the end. So, even if it is not fun, I ask that you complete the lectures.
Learning Objectives
You can try developing a deep learning program yourself.
Helpful people
For those who want to get started with deep learning but find it difficult because of the complicated terminology and theories
For those who still don't understand even after looking through books or other examples
For those who need to develop a deep learning-based program but have difficulty finding a starting point
For those who need to understand the theoretical background, but have some practical development
Those who have developed based on TensorFlow but are new to Keras
A course that is not even worth 1 star
First, I doubt whether the lecturer understands deep learning and teaches it.
I think there are people who have sufficient knowledge but poor communication skills, and on the contrary, there are people who do not have sufficient knowledge but have good communication skills and make good lectures. However, the person who taught this course had no communication skills and seemed to have very low related knowledge. I also think that he was not prepared for the class.
1. No understanding of why relu is used and back propagation
2. As a programmer, when explaining other people's code, no awareness of copyright
3. Just reading the code to explain the example, without knowing what the problem is or what it is to solve
4. I wonder why the title is Keras Lecture
5. Excessive explanation only for parts that anyone can understand
6. When explaining the model, refer to the wiki and Keras documentation, and roughly skip over them for those who are curious
7. All theoretical explanations are just a guess
8. Etc.
Still, "Extension" and "Diagnosis" made me laugh out loud.
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