Programming assignments and quizzes from all courses in the Coursera Deep Learning specialization offered by deeplearning.ai.
Instructor: Andrew Ng
For detailed interview-ready notes on all courses in the Coursera Deep Learning specialization, refer www.aman.ai.
Run setup.sh to (i) download a pre-trained VGG-19 dataset and (ii) extract the zip'd pre-trained models and datasets that are needed for all the assignments.
This repo contains my work for this specialization. The code base, quiz questions and diagrams are taken from the Deep Learning Specialization on Coursera, unless specified otherwise.
This specialization was updated in April 2021 to include developments in deep learning and programming frameworks, with the biggest change being shifting from TensorFlow 1 to TensorFlow 2. This repo has been updated accordingly as well.
- Week 2 - PA 1 - Python Basics with Numpy
- Week 2 - PA 2 - Logistic Regression with a Neural Network mindset
- Week 3 - PA 3 - Planar data classification with one hidden layer
- Week 4 - PA 4 - Building your Deep Neural Network: Step by Step
- Week 4 - PA 5 - Deep Neural Network for Image Classification: Application
- Week 1 - PA 1 - Initialization
- Week 1 - PA 2 - Regularization
- Week 1 - PA 3 - Gradient Checking
- Week 2 - PA 4 - Optimization Methods
- Week 3 - PA 5 - TensorFlow Tutorial
- There are no programming assignments for this course. But this course comes with very interesting case study quizzes (below).
- Week 1 - PA 1 - Convolutional Model: step by step
- Week 1 - PA 2 - Convolutional Neural Networks: Application
- Week 2 - PA 1 - Keras - Tutorial - Happy House
- Week 2 - PA 2 - Residual Networks
- Week 2 - PA 2 - Transfer Learning with MobileNet
- Week 3 - PA 1 - Car detection with YOLO for Autonomous Driving
- Week 3 - PA 2 - Image Segmentation Unet
- Week 4 - PA 1 - Art Generation with Neural Style Transfer
- Week 4 - PA 2 - Face Recognition
- Week 1 - PA 1 - Building a Recurrent Neural Network - Step by Step
- Week 1 - PA 2 - Dinosaur Land -- Character-level Language Modeling
- Week 1 - PA 3 - Jazz improvisation with LSTM
- Week 2 - PA 1 - Word Vector Representation and Debiasing
- Week 2 - PA 2 - Emojify!
- Week 3 - PA 1 - Neural Machine Translation with Attention
- Week 3 - PA 2 - Trigger Word Detection
- Week 4 - PA 1 - Transformer Network
- Week 3 - PA 2 - Transformer Network Application: Named-Entity Recognition
- Week 3 - PA 2 - Transformer Network Application: Question Answering
- Week 1 Quiz - Introduction to deep learning: Text | PDF
- Week 2 Quiz - Neural Network Basics: Text | PDF
- Week 3 Quiz - Shallow Neural Networks: Text | PDF
- Week 4 Quiz - Key concepts on Deep Neural Networks: Text | PDF
- Week 1 Quiz - Practical aspects of deep learning: Text | PDF
- Week 2 Quiz - Optimization algorithms: Text | PDF
- Week 3 Quiz - Hyperparameter tuning, Batch Normalization, Programming Frameworks: Text | PDF
- Week 1 Quiz - Bird recognition in the city of Peacetopia (case study): Text | PDF
- Week 2 Quiz - Autonomous driving (case study): Text | PDF
- Week 1 Quiz - The basics of ConvNets: Text | PDF
- Week 2 Quiz - Deep convolutional models: Text | PDF
- Week 3 Quiz - Detection algorithms: Text | PDF
- Week 4 Quiz - Special applications: Face recognition & Neural style transfer: Text | PDF
- Week 1 Quiz - Recurrent Neural Networks: Text | PDF
- Week 2 Quiz - Natural Language Processing & Word Embeddings: PDF
- Week 3 Quiz - Sequence models & Attention mechanism: Text | PDF
I recognize the time people spend on building intuition, understanding new concepts and debugging assignments. The solutions uploaded here are only for reference. They are meant to unblock you if you get stuck somewhere. Please do not copy any part of the code as-is (the programming assignments are fairly easy if you read the instructions carefully). Similarly, try out the quizzes yourself before you refer to the quiz solutions. This course is the most straight-forward deep learning course I have ever taken, with fabulous course content and structure. It's a treasure by the deeplearning.ai team.
