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Deep Learning Specialization on Coursera

Master Deep Learning, and Break into AI

Instructor: Andrew Ng

Introduction

This repo contains all my programming assignments. I transcripted all the problems to google colab to being everything more reproducible.

¿What is colab?

Google colab is a free cloud service (jupyter as service) with GPU and TPU support.

Course 01: Neural Networks and Deep Learning

Logistic Regression (Week02)

Run in Google Colab View source on GitHub

Shallow Neural Networks (Week03)

Run in Google Colab View source on GitHub

Deep Neural Networks - Building (Week04)

Run in Google Colab View source on GitHub

Deep Neural Networks - Application (Week04)

Run in Google Colab View source on GitHub

Course 02: Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization

Practical aspects of Deep Learning (Week01)

Gradient Checking

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Initialization

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Regularization

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Optimization algorithms (Week02)

Run in Google Colab View source on GitHub

Hyperparameter tuning, Batch Normalization and Programming Frameworks (Week03)

Run in Google Colab View source on GitHub

Course 03: Structuring Machine Learning Projects

Course 04: Convolutional Neural Networks

Foundations of Convolutional Neural Networks (Week01)

Run in Google Colab View source on GitHub

Foundations of Convolutional Neural Networks (Week01)

Run in Google Colab View source on GitHub

Deep convolutional models: case studies (Week02)

Keras Tutorial - The Happy House (not graded)

Run in Google Colab View source on GitHub

Residual Networks

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Object detection (Week03)

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Face recognition & Neural style transfer (Week04)

Art generation with Neural Style Transfer

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Face Recognition for the Happy House

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