: This repo contains all my work for this specialization of Andrew Ng's deep learning course on Coursera
This course is consist of 5 sub-courses covering from basic of neural networks to convolutional neural networks and sequence models. Each course has 3 or 4 weeks of materials including the quiz and the code assignment (which was the greatest part of this course).
If you'd like to know how I finish this course with the most efficiency, feel free to check How I Finished Andrew Ng’s Deep Learning Specialization in Just 4 Weeks on Medium.
certifications
Course 1: Neural Networks and Deep Learning
- Week 2-1 : Python Basics With Numpy v3
- Week 2-2 : Logistic Regression with a Nueral Network mindset V5
- Week 3 : Planar data classification with one hidden layer v5
- Week 4-1 : Building your Deep Neural Network: Step by Step
- Week 4-2 : Deep Neural Network for Image Classification: Application
Course 2: Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
- Week 1-1 : initialization
- Week 1-2 : Regularization v2
- Week 1-3 : Gradient Checking v1
- Week 2-1 : Optimization methods
- Week 3-1 : Tensorflow Tutorial
Course 3: Structuring Machine Learning Projects
- Week 1 : Bird recognition in the city of Peacetopia
- Week 2 : Autonomous driving
Course 4: Convolutional Neural Networks
- Week 1-1 : Convolution model: Step by Step v2
- Week 1-1 : Convolution model: Application v1
- Week 2-1 : Keras Tutorial-Happy House v2
- Week 2-2 : Residual Networks v2
- Week 3 : Autonomous driving application-Car detection v3
- Week 4-1 : Art Generation with Neural Style Transfer v2
- Week 4-2 : Face Recognition for the Happy House v3
Course 5: Sequence Models
- Week 1-1 : Building a Recurrent Neural Network-Step by Step v3
- Week 1-2 : Dinosaurus Island-Character level language model final v3
- Week 1-3 : Improvise a Jazz Solo with an LSTM Network v3
- Week 2-1 : Operations on word vectors v2
- Week 2-1 : Emojify v2
- week 3-1 : Neural machine translation with attention v4
- week 3-2 : Trigger word detection v1