TensorFlow tutorials that choose clarity over cleverness

What it does

This repository holds companion lab exercises for introductory deep-learning video tutorials taught in Korean. The scripts walk through basic TensorFlow, Keras, and MXNet concepts as plain Python files organized by lesson number. It is explicitly built for instruction, not production workloads.

The interesting bit

The maintainers enforce a strict readability-over-efficiency rule and openly cite the KISS principle in their style guide. That is a rare admission in a field that usually worships benchmark bragging rights.

Key highlights

• Parallel labs for TensorFlow, Keras, and MXNet, distinguished by lab-, klab-, and mxlab- file prefixes.
• Style guide demands “More TF (1.0) style,” Pythonic patterns, and understandability above all else.
• Companion slides are available through a shared Google link.
• Openly flagged as work in progress and actively welcomes comments and pull requests.

Caveats

• Code targets TensorFlow 1.0-era APIs, so some patterns will feel dated compared with current TensorFlow versions.
• Authors warn the repo may contain bugs and that test coverage is still incomplete.

Verdict

Best for students who learn by following video lectures and reading straightforward, unoptimized code. Look elsewhere if you need state-of-the-art reference implementations or production-ready pipelines.