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Deep Learning Foundation and Concepts(DLFaC) Learning Notes

Deep Learning Foundation and Concepts(DLFaC) Learning Notes

This page contains all the learning notes for the Deep Learning Foundation and Concepts (DLFaC) course. I hope you can find something useful here. HAPPY LEARNING😁😁!!!
Note

Due to the time constraint, these notes may contain errors or omissions. And to speed up the writing process, I only wrote the notes in CHINESES. If you are interested in collaborating to improve these notes,or transalting to different languages, please feel free to contact me.

Related Resources:

  • Book Website: Deep Learning Foundations and Concepts
  • My GitHub Repo: GitHub


Chapter 01: Introduction to the Deep Learning

Chapter 01 主要介绍了什么Deep Learning 与其的应用,并且通过一个简单的 Polynomial Regression 例子来说明 Deep Learning 模型训练的基本流程。通过Chapter 01的学习,读者可以初步了解深度学习的基本概念、应用领域以及模型训练的基本步骤。

Yuyang Zhang
 

Chapter 02: Probabilities & Information Theory

Chapter 02 介绍了概率论和信息论的基本概念,包括随机变量、概率分布、条件概率、熵等内容。这些概念在深度学习中尤为重要,因为它们帮助我们理解模型如何处理不确定性和信息。

Yuyang Zhang
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