![처음하는 딥러닝과 파이토치(Pytorch) 부트캠프 (쉽게! 기본부터 챗GPT 핵심 트랜스포머까지) [데이터분석/과학 Part3]강의 썸네일](https://cdn.inflearn.com/public/courses/329540/cover/1be7b8cb-800f-48cb-a30c-b7d78996c075/329540-eng.png?w=420)
처음하는 딥러닝과 파이토치(Pytorch) 부트캠프 (쉽게! 기본부터 챗GPT 핵심 트랜스포머까지) [데이터분석/과학 Part3]
잔재미코딩 DaveLee
강사가 처음 딥러닝을 익혔을 때 실패했던 경험을 바탕으로 딥러닝 이해에 필요한 수학, 이론, 파이토치 기반 구현, 전이학습, GPT 핵심 트랜스포머까지 차근차근 익힐 수 있도록 새롭게 꾸민 강의입니다.
초급
딥러닝, PyTorch, 머신러닝
This course conducts hands-on practice related to Diffusion models among generative artificial intelligence models. By reading and implementing the prompt-to-prompt paper, which is a representative Diffusion model application paper, we expect to cultivate the ability to understand the latest artificial intelligence papers.
49 learners
Understanding Diffusion Model Concepts
Understanding the Prompt-to-prompt Paper: A Representative Diffusion Model Application
Implementing the Prompt-to-prompt Paper Using PyTorch
Solutions for Overcoming Obstacles When Reading and Implementing AI Papers
Who is this course right for?
Everyone involved in projects implementing the content of the latest artificial intelligence papers
Those preparing for AI-related careers (AI engineers, AI graduate school, etc.)
Those preparing university graduation thesis/projects on the topic of artificial intelligence
Need to know before starting?
Understanding of the Python Language
Basic development experience using Visual Studio Code, Anaconda, and Jupyter Notebook
Basic understanding of linear algebra/artificial intelligence
All
53 lectures ∙ (6hr 32min)
Course Materials:
5. Diffusion Process
02:56
16. Abstract
13:57
20. Related work
09:02
21. Method (1/9)
05:44
22. Method (2/9)
10:59
23. Method (3/9)
11:22
24. Method (4/9)
13:49
25. Method (5/9)
04:39
26. Method (6/9)
17:04
27. Method (7/9)
12:21
28. Method (8/9)
05:37
29. Method (9/9)
03:31
37. Conclusions
09:32
All
4 reviews
5.0
4 reviews
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$29,700.00
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$30.80
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