
모두를 위한 대규모 언어 모델 LLM(Large Language Model) Part 1 - Llama 2 Fine-Tuning 해보기
AISchool
LLM(Large Language Model)의 기초 개념부터 고성능 LLM인 Llama 2 모델을 내가 원하는 데이터셋에 Fine-Tuning하는 방법까지 차근차근 학습합니다.
중급이상
LLM, Llama, 딥러닝
This course teaches you how to implement deep learning papers by implementing the U-Net paper from scratch using TensorFlow 2.0.

How to read deep learning papers
How to implement deep learning papers
Detailed understanding of the U-Net model structure
Background knowledge on the Semantic Image Segmentation problem domain
How to write code using TensorFlow 2.0
An essential skill for deep learning researchers: the ability to implement the latest research papers!
Learn with U-Net implementation 😀
Many companies, when hiring deep learning researchers, value experience implementing cutting-edge research papers . Gain hands-on experience implementing the U-Net (U-Net: Convolutional Networks for Biomedical Image Segmentation) paper and gain hands-on experience implementing cutting-edge research papers .
After reading the U-Net paper together and fully understanding the U-Net structure✍️,
Let's implement U-Net ourselves using TensorFlow 2.0.👨🏻💻
We'll read the U-Net paper (U-Net: Convolutional Networks for Biomedical Image Segmentation) and implement the U-Net model from scratch using TensorFlow 2.0 . We'll also use the implemented U-Net model to create a medical image (ISBI-2012) segmentation model.
👋 This course requires prior knowledge of TensorFlow 2.0 and the fundamentals of deep learning. Please take the following courses first, or obtain equivalent knowledge before taking this course .
This course teaches you the core theories of deep learning and how to implement deep learning code using the latest TensorFlow 2.0.
Q. What are the benefits of experiencing implementing deep learning papers?
Who is this course right for?
Those who want to develop the ability to read and implement deep learning papers
Those who want to get a job related to deep learning research
Anyone who wants to conduct research related to artificial intelligence/deep learning
Those preparing for graduate school in artificial intelligence (AI)
Need to know before starting?
Experience using Python
Experience of attending the pre-course [Introduction to Deep Learning with TensorFlow 2.0]
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23 lectures ∙ (2hr 46min)
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