TensorFlow-Tutorials

Why we included this project

Each folder in this repo is a small, self-contained example you can run and modify, which is closer to how most people actually learn TensorFlow than reading a textbook. The topics climb from linear regression and MNIST to CNN, autoencoder, GAN, RNN, seq2seq, Inception, and DQN, with scripts kept deliberately short and readable. Since every comment is in Korean, it is most obviously useful to Korean speakers starting out, though the code itself is plain Python anyone can follow. The author keeps theory light and implementation simple on purpose, so the collection reads like a survey of the major model families before you commit to learning any one deeply. One caveat: it is built for TensorFlow 1.x, so treat it as a way to grasp fundamentals, not as a codebase to drop into a current project.