Reviews
The general content is a lot of good. The example problems were not usually bad either. However, the mathematical approach is not very well explained. The narratives are not precise. In the case of technology that is difficult to transmit or access, it is better to take off or write down reference documents. But, in the case of Deeping blogs, the content of famous foreign authors is much more helpful to understanding than our country.
And it's very helpful to those of you who are deep-dating students. It's very well-organized, so it's good to follow.
I was studying machine learning. And I was curious about the popular Deepings these days. So I chose this book. DN, 01, RNP, KAN, etc., and so on. And it was great to know how to apply the Tensaple. It's nice to have all of this in a chart of Florou, which looks very different from the other books. And it was very easy to read because it was so good.
Because we didn't do data-analysis work, we had to learn basic theories and implements, and we were able to learn everything we needed from this book. We learned to take perfect deep-diving, to make sure we understood the theory and to use the Tensaple. And especially since the basic grammar of Tensaplelo, it's very helpful for those who can't code by giving you a quick, quick presentation. It's hard for a beginner to study deep-ding.
Seo Ji-young: Deep Learning TensorFlow Textbook
From the machine running core algorithm, focus on understanding the idea of deep-down algorithms such as multi-synthetic nerve networks, 01, circulatory neural networks, and LSTM, and see when and what is the best way to use each algorithm. Also, there is a long list of concepts that should be learned, done in natural languages, clock sequences, reinforced learning, and GAN, other than basic algorithms. After learning each concept, you can try to implement it directly with a tenaple two and make sure you understand the concept, the way it works and the extent of its application.
Korean title: 딥러닝 텐서플로 교과서
Korean author: 서지영
Korean publisher: 길벗
ISBN-13: 9791165215477
Reviews
The general content is a lot of good. The example problems were not usually bad either. However, the mathematical approach is not very well explained. The narratives are not precise. In the case of technology that is difficult to transmit or access, it is better to take off or write down reference documents. But, in the case of Deeping blogs, the content of famous foreign authors is much more helpful to understanding than our country.
And it's very helpful to those of you who are deep-dating students. It's very well-organized, so it's good to follow.
I was studying machine learning. And I was curious about the popular Deepings these days. So I chose this book. DN, 01, RNP, KAN, etc., and so on. And it was great to know how to apply the Tensaple. It's nice to have all of this in a chart of Florou, which looks very different from the other books. And it was very easy to read because it was so good.
Because we didn't do data-analysis work, we had to learn basic theories and implements, and we were able to learn everything we needed from this book. We learned to take perfect deep-diving, to make sure we understood the theory and to use the Tensaple. And especially since the basic grammar of Tensaplelo, it's very helpful for those who can't code by giving you a quick, quick presentation. It's hard for a beginner to study deep-ding.
