Lessons for AI Laboratory

This repository contains the lessons that I gave for the laboratory I belonged to. The original repository is this and this repository includes only the lessons I built. It can be divided into mostly 4 parts: M1_spring, M1_autumn, M2_spring, and M2_autumn, where the number and the latter word indicate an academic year of master's degree (when I created the lessons) and the semester, respectively.

Lessons

M1_spring

• 02_Learning_Algorithm
  • It describes the basic algorithm used in machine learning.
• 04_Overfitting_Underfitting
• 05_Practice-Overfitting_Underfitting
  • It contains an exercise of the lesson regaring overfitting and underfitting.
• 10_Convolutional_Neural_Networks

M1_autumn

• PyTorch_implementation

M2_spring

• PyTorch_implementation

M2_autumn

• Auto-Encoder

Docker Environment

This repository contains docker environment to allow anyone to try my model. To make the execution simple, I created my environment with docker-compose. Please follow the procedure below to build my environment.

1. Go to Docker/
2. docker-compose up -d
3. docker-compose exec gonken-lesson nohup jupyter lab --ip=0.0.0.0 --no-browser --allow-root --NotebookApp.token='' --port 8080
4. Go to http://localhost:8080/lab