Deep Learning Specialization on Coursera

Master Deep Learning, and Break into AI💪

Instructor: Andrew Ng

deeplearning.ai

Introduction

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. There are also additional materials for references:kissing_heart:.

Tools and Frameworks used::point_down:

About This Specialization:yum::sunglasses::blush:

If you want to break into AI, this Specialization will help you do so. Deep Learning is one of the most highly sought after skills in tech. We will help you become good at Deep Learning.

In five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. You will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing. You will master not only the theory, but also see how it is applied in industry. You will practice all these ideas in Python and in TensorFlow, which we will teach.

You will also hear from many top leaders in Deep Learning, who will share with you their personal stories and give you career advice.

AI is transforming multiple industries. After finishing this specialization, you will likely find creative ways to apply it to your work.

We will help you master Deep Learning, understand how to apply it, and build a career in AI.

Course 1: Neural Networks and Deep Learning:smiley:

Week 1: Quiz: Introduction to deep learning

Week 2: Quiz: Neural Network Basics || Practice Programming Assignment: Python Basics with numpy (optional) || Programming Assignment: Logistic Regression with a Neural Network mindset

Week 3: Quiz: Shallow Neural Networks || Programming Assignment: Planar data classification with a hidden layer

Week 4: Quiz: Key concepts on Deep Neural Networks || Programming Assignment: Building your deep neural network: Step by Step || Programming Assignment: Deep Neural Network Application

Course 2: Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization:flushed:

Week 1: Quiz: Practical aspects of deep learning || Programming Assignment: Initialization || Programming Assignment: Regularization || Programming Assignment: Gradient Checking

Week 2: Quiz: Optimization algorithms || Programming Assignment: Optimization

Week 3: Quiz: Hyperparameter tuning, Batch Normalization, Programming Frameworks || Programming Assignment: Tensorflow

Course 3: Structuring Machine Learning Projects:kissing_smiling_eyes:

Week 1: Quiz: Bird recognition in the city of Peacetopia (case study)

Week 2: Quiz: Autonomous driving (case study)

Course 4: Convolutional Neural Networks:sweat_smile:

Week 1: Quiz: The basics of ConvNets || Programming Assignment: Convolutional Model: step by step || Programming Assignment: Convolutional model: application

Week 2: Quiz: Deep convolutional models || Keras Tutorial - The Happy House (not graded) || Programming Assignment: Residual Networks

Week 3: Quiz: Detection algorithms || Programming Assignment: Car detection with YOLOv2

Week 4: Quiz: Special applications: Face recognition & Neural style transfer || Programming Assignment: Art generation with Neural Style Transfer || Programming Assignment: Face Recognition for the Happy House

Course 5: Sequence Models:heart_eyes:

Week 1: Quiz: Recurrent Neural Networks || Programming Assignment: Building a recurrent neural network - step by step || Programming Assignment: Dinosaur Island - Character-Level Language Modeling || Programming Assignment: Jazz improvisation with LSTM

Week 2: Quiz: Natural Language Processing & Word Embeddings || Programming Assignment: Operations on word vectors - Debiasing || Programming Assignment: Emojify

Week 3: Quiz: Sequence models & Attention mechanism || Programming Assignment: Neural Machine Translation with Attention || Programming Assignment: Trigger word detection