Deep Learning course for humanists

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1. Introduction
- 1.1 Introduction
- 1.2 Environment Setup
2. Perceptron
- 2.1 Foundation block of Neural Network—Perceptron
- 2.2 Iris Classification
3. Multilayer Perceptron
- 3.1 Multilayer Perceptron
- 3.2 Activate Function
4. Forward Propagation
5. Training Neural Networks
- 5.1 How well does the neural network predict?—Loss Function
- 5.2 Learning to minimize error—Gradient Descent Method

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Introduction

In this chapter, we will first introduce artificial intelligence, machine learning, deep learning and their relationship. Then, teach how to set up the environment needed for the course.

Introduction
Environment Setup

〈 GitHub repository Introduction 〉