DeepLearning-Tutorial/current_materials at main · Sangh0/DeepLearning-Tutorial

Name	Name	Last commit message	Last commit date
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1_python_for_beginners.ipynb	1_python_for_beginners.ipynb
2_python_review_with_baekjoon.ipynb	2_python_review_with_baekjoon.ipynb
3_linear_regression_and_classification.ipynb	3_linear_regression_and_classification.ipynb
4_gradient_descent.ipynb	4_gradient_descent.ipynb
5_dnn_with_mnist.ipynb	5_dnn_with_mnist.ipynb
6_cnn_with_mnist.ipynb	6_cnn_with_mnist.ipynb
7_overfitting_and_gap.ipynb	7_overfitting_and_gap.ipynb
8_implement_vgg_network.ipynb	8_implement_vgg_network.ipynb
9_fine_tuning_llm.ipynb	9_fine_tuning_llm.ipynb
README.md	README.md

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Introduce Machine Learning and Deep Learning for begineers

Contents

The materials are composed of colab files
Chapter 1. Python Introduction
- From string and number variable assignments to class of Python
- material
Chapter 2. Python with Baekjoon practices
- Baekjoon practice
- material
Chatper 3. Linear regression and classification
- material
Chapter 4. Gradient Descent
- material
Chapter 5. Building and Training Multi Layer Perceptron
- material
Chapter 6. Building and Training Convolutional Neural Network
- material