/deeplearning.ai

From deeplearning.ai, "Deep Learning Specialization" taught by Andrew Ng, on Coursera

Primary LanguageJupyter Notebook

deeplearning.ai - Deep Learning Specialization on Coursera

Instructor: Andrew Ng

Introduction

This repository contains all the programming projects for this 5-course deep learning specialization. Some multimedia files have not been included with the corresponding Jupyter notebooks.

Course 5, Sequence Models, is all about deep learning for Natural Language Processing (NLP). Many popular topics in this domain are covered, such as Character-level Language Modeling, Sentiment Analysis, Neural Machine Translation and Trigger Word Detection. The programming assignments I completed are closely related to those topics. Common deep neural networks, such as Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Long Short-Term Memory(LSTM), Bi-directional LSTM and GRU have been used along the programming exercise.

Programming Assignments

  • Course 1: Neural Networks and Deep Learning

    • Week 2 - PA 1 - Python Basics with Numpy
    • Week 2 - PA 2 - Logistic Regression with a Neural Network
    • Week 3 - PA 1 - Planar data classification with one hidden layer
    • Week 4 - PA 1 - Building your Deep Neural Network: Step by Step
    • Week 4 - PA 2 - Deep Neural Network for Image Classification: Image Classification

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

    • Week 1 - PA 1 - Initialization
    • Week 1 - PA 2 - Regularization
    • Week 1 - PA 3 - Gradient Checking
    • Week 2 - PA 1 - Optimization Methods
    • Week 3 - PA 1 - TensorFlow Tutorial

  • Course 3: Structuring Machine Learning Projects

    • No Programming Assignments for this course.

  • Course 4: Convolutional Neural Networks

    • Week 1 - PA 1 - Convolutional Model: step by step (CNN)
    • Week 1 - PA 2 - Convolutional Model: Build and train a ConvNet in TensorFlow for a classification problem with the SIGNS dataset
    • Week 2 - PA 1 - Keras - Tutorial - Happy House
    • Week 2 - PA 2 - Residual Networks
    • Week 3 - PA 1 - Car Detection for Autonomous Driving
    • Week 4 - PA 1 - Face Recognition (Keras)
    • Week 4 - PA 2 - Neural Style Transfer

  • Course 5: Sequence Models for Natural Language Processing (NLP)

    • Week 1 - PA 1 - Building a Recurrent Neural Network - Step by Step
    • Week 1 - PA 2 - Dinosaurus land - Character-level Language Modeling
    • Week 1 - PA 3 - Jazz improvisation with LSTM
    • Week 2 - PA 1 - Operations on Word Vectors - Debiasing
    • Week 2 - PA 2 - Emojify (LSTM, word embeddings with Keras)
    • Week 3 - PA 1 - Neural Machine Translation with Attention (LSTM, Bi-LSTM, Attention mechanism)
    • Week 3 - PA 2 - Trigger Word Detection (GRU with Keras)