Learning Deep Learning Paper Implementation through GPT Paper Implementation with TensorFlow 2.0 Part 1

A course to learn deep learning paper implementation skills, implementing the GPT-1 (Improving Language Understanding by Generative Pre-Training) paper from scratch with TensorFlow 2.0.

(1.0) 1 reviews

49 learners

Level Intermediate

Course period Unlimited

gpt
gpt
Tensorflow
Tensorflow
Deep Learning(DL)
Deep Learning(DL)
gpt
gpt
Tensorflow
Tensorflow
Deep Learning(DL)
Deep Learning(DL)
날개 달린 동전

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날개 달린 동전

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What you will gain after the course

  • How to Read Deep Learning Papers

  • How to implement Deep Learning papers

  • Detailed Understanding of GPT (Generative Pre-trained Transformer) Model Structure

  • GPT (Generative Pre-trained Transformer) Model Background

  • Coding with TensorFlow 2.0

An essential skill for deep learning researchers: the ability to implement the latest research papers!
Learn with GPT implementation 😀

Implementing the latest papers with GPT!

When hiring deep learning researchers, many companies give preference to those with experience implementing the latest papers .
Gain experience implementing the latest papers by implementing the GPT-1 (Improving Language Understanding by Generative Pre-Training) paper yourself.

Understanding the structure of GPT-1 with the paper + implementing it directly with TensorFlow 2.0!

  • ✍️ After reading the GPT-1 paper and fully understanding its structure,
  • 👨🏻‍💻 Implementing GPT-1 directly with TensorFlow 2.0.

We will read the GPT-1 paper (Improving Language Understanding by Generative Pre-Training) and implement the GPT-1 model from scratch using TensorFlow 2.0 .


Player lectures

👋 This course requires prior knowledge of TensorFlow 2.0 and natural language processing (NLP) . Be sure to take the courses below first or have equivalent knowledge before taking this course.

Expected Questions Q&A 💬

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

Recommended for
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Who is this course right for?

  • Those wishing to develop deep learning paper reading and implementation skills.

  • Individuals aspiring to deep learning research roles.

  • Those who wish to conduct AI/Deep Learning research

  • AI Graduate School Preparers

Need to know before starting?

  • Python experience

  • Prior Course: [Introduction to Deep Learning Natural Language Processing with Examples: NLP with TensorFlow - From RNN to BERT] Course Experience

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30 lectures ∙ (4hr 27min)

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  • kordokrip님의 프로필 이미지
    kordokrip

    Reviews 21

    Average Rating 3.7

    1

    57% enrolled

    This isn't just a lecture that reads the open AI GPT-1 paper... There's no material, and the freelancing that passed this as a lecture is also...

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