Completed notebooks for Andrew Ng's deep-learning MOOC

What it does

This repository is a single student’s collected coursework for Andrew Ng’s five-course Deep Learning Specialization on Coursera. It holds Jupyter notebooks walking through the programming assignments—from logistic regression and shallow neural networks up to CNNs, ResNets, and character-level RNNs—plus markdown quiz solutions for the first three courses. The author explicitly warns that the material is “only for your reference purpose” and asks visitors not to copy code before attempting the assignments themselves.

The interesting bit

With 7,731 stars, this is essentially one of GitHub’s most popular answer keys. The author stopped updating quiz solutions after Course 3 because they realized people were using the repo to “quickly ace the course” without doing the work, which gives you a good idea of how most visitors actually use it. Even the author admits the MOOC is “almost the simplest deep learning course” they have taken, which makes the repo’s popularity as a crutch all the more telling.

Key highlights

• Covers all five specialization courses: Neural Networks, Hyperparameter Tuning, Structuring ML Projects, CNNs, and Sequence Models
• Programming assignments include step-by-step network construction, Keras and TensorFlow tutorials, Residual Networks, and a character-level language model
• Quiz solutions are only available for Courses 1–3; the author halted updates to discourage cheating
• Noted milestone: the first three courses were completed back in August 2017
• Slide screenshots and notes were started then abandoned (struck through in the README)

Caveats

• Quiz solutions for Courses 4 and 5 are crossed out and unavailable
• Slide note archives were begun then abandoned
• This is purely coursework reference, not a reusable library or framework

Verdict

Handy if you’re currently enrolled and need a sanity check when your Gradient Checking assignment fails, but skip it entirely if you’re hunting for original tools or research code.