September 4, 2019

699 words 4 mins read



Deep Learning Specialization by Andrew Ng on Coursera.

repo name Kulbear/deep-learning-coursera
repo link
language Jupyter Notebook
size (curr.) 49757 kB
stars (curr.) 4899
created 2017-08-09
license MIT License

Deep Learning Specialization on Coursera

Master Deep Learning, and Break into AI

Instructor: Andrew Ng


This repo contains all my work for this specialization. All the code base, quiz questions, screenshot, and images, are taken from, unless specified, Deep Learning Specialization on Coursera.

What I want to say


As a CS major student and a long-time self-taught learner, I have completed many CS related MOOCs on Coursera, Udacity, Udemy, and Edx. I do understand the hard time you spend on understanding new concepts and debugging your program. There are discussion forums on most MOOC platforms, however, even a question with detailed description may need some time to be answered. Here I released these solutions, which are only for your reference purpose. It may help you to save some time. And I hope you don’t copy any part of the code (the programming assignments are fairly easy if you read the instructions carefully), see the quiz solutions before you start your own adventure. This course is almost the simplest deep learning course I have ever taken, but the simplicity is based on the fabulous course content and structure. It’s a treasure given by team.

Currently, this repo has 3 major parts you may be interested in and I will give a list here.

Programming Assignments

Quiz Solutions

There are concerns that some people may use the content here to quickly ace the course so I’ll no longer update any quiz solution.

- Course 4: Convolutional Neural Networks - Course 5: Sequence Models

## Important Slide Notes

I screenshotted some important slide page and store them into GitHub issues. It seems not very helpful for everyone since I only keep those I think may be useful to me.

- Screenshots for Course 1: Neural Networks and Deep Learning

- Screenshots for Course 2: Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization

- Screenshots for Course 3: Structuring Machine Learning Projects

- Screenshots for Course 4: Convolutional Neural Networks

- Screenshots for Course 5: Sequence Models


  • 2017-08-17: Finished the first-released 3 courses, YAY! 😈
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