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Deep Learning Paper Implementation with U-Net Implementation with TensorFlow 2.0 - Deep Learning Medical Image Analysis

This course teaches you how to implement deep learning papers by implementing the U-Net paper from scratch using TensorFlow 2.0.

(4.4) 7 reviews

124 learners

  • AISchool
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Tensorflow
Deep Learning(DL)

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What you will learn!

  • 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 😀

Implementing the latest papers with U-Net!

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 .

Understanding the structure with the U-Net paper + implementing it directly with TensorFlow 2.0!

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.

✅ Player lectures

👋 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 .

Introduction to Deep Learning with TensorFlow 2.0

This course teaches you the core theories of deep learning and how to implement deep learning code using the latest TensorFlow 2.0.

Expected Questions Q&A 💬

Q. What are the benefits of experiencing implementing deep learning papers?

Recommended for
these people

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]

Hello
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9,089

Learners

670

Reviews

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Answers

4.6

Rating

29

Courses

Curriculum

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23 lectures ∙ (2hr 46min)

Course Materials:

Lecture resources
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Reviews

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7 reviews

4.4

7 reviews

  • apple3430님의 프로필 이미지
    apple3430

    Reviews 2

    Average Rating 4.0

    4

    100% enrolled

    • Soyoung님의 프로필 이미지
      Soyoung

      Reviews 1

      Average Rating 5.0

      5

      61% enrolled

      자세히 하나하나 설명해주고 논문 해석 방법도 알려줘서 너무 좋아요!

      • 이현희님의 프로필 이미지
        이현희

        Reviews 2

        Average Rating 5.0

        5

        100% enrolled

        차분하고 차근차근 잘 알려주셔서 이해가 잘 됩니다! 추천드려요

        • 김종민님의 프로필 이미지
          김종민

          Reviews 1

          Average Rating 5.0

          5

          100% enrolled

          논문이랑 코드 내용이랑 같이 나란히 놓고 설명해주면 더 잘 이해할 거 같아요

          • hyunsik님의 프로필 이미지
            hyunsik

            Reviews 3

            Average Rating 4.7

            5

            100% enrolled

            잘 들었습니다.

            $77.00

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