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· 제목 : Practical MATLAB Deep Learning: A Projects-Based Approach (Paperback, 2)
· 분류 : 외국도서 > 컴퓨터 > 인공지능(AI)
· ISBN : 9781484279113
· 쪽수 : 329쪽
· 출판일 : 2022-09-11
· 분류 : 외국도서 > 컴퓨터 > 인공지능(AI)
· ISBN : 9781484279113
· 쪽수 : 329쪽
· 출판일 : 2022-09-11
목차
1. What is deep learning? ? no changes except editorial
a. Machine learning vs. deep learning
b. Approaches to deep learning
c. Recurrent deep learning
d. Convolutional deep learning
2. MATLAB machine and deep learning toolboxes
a. Describe the functionality and applications of each toolbox
b. Demonstrate MATLAB toolboxes related to Deep Learning
c. Include the text toolbox generative toolbox and reinforcement learning toolbox
d. Add more detail on each
3. Finding Circles ? no changes except editorial.
4. Classifying movies ? no changes except editorial.
5. Tokamak disruption detection ? this would be updated.
6. Classifying a pirouette ? no changes except editorial.
7. Completing sentences - This would be revamped using the MATLAB Text Processing Toolbox.
8. Terrain based navigation-The example in the original book would be changed to a regression approach that can interpolate position. We would switch to a terrestrial example applicable to drones.9. Stock prediction ? this is a very popular chapter. We would improve the algorithm.
10. Image classification ? no changes except editorial.
11. Orbit Determination ? add inclination to the algorithm.
12. Earth Sensors ? a new example on how to use neural networks to measure roll and yaw from any Earth sensor.13. Generative deep learning example. This would be a neural network that generates pictures after learning an artist’s style.
14. Reinforcement learning. This would be a simple quadcopter hovering control system. It would be simulation based although readers would be able to apply this to any programmable quadcopter.
