zmyzheng/Neural-Networks-and-Deep-Learning

Deep learning projects including applications (face recognition, neural style transfer, autonomous driving, sign language reading, music generation, translation, speech recognition and NLP) and theories (CNNs, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, hyperparameter tuning, regularization, optimization, Residual Networks). Deep Learning Specialization by Andrew Ng, deeplearning.ai

Neural-Networks-and-Deep-Learning

Introduction

This repo contains deep learning projects for Deep Learning Specialization on Coursera. These projects cover different aspects of nerual networks and deep learning, including theories (CNNs, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, hyperparameter tuning, regularization, optimization, Residual Networks, and more) and applications (face recognition, neural style transfer, autonomous driving, sign language reading, music generation, translation, speech recognition and natural language processing).

Projects

There are 4 parts in this repository:

• Part 1: Basis of Neural Networks and Deep Learning

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

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

  • 1 - Initialization
  • 2 - Regularization
  • 3 - Gradient Checking
  • 4 - Optimization Methods
  • 5 - TensorFlow Tutorial

• Part 3: Convolutional Neural Networks

  • 1 - Convolutional Model: step by step
  • 2 - Convolutional Model: application
  • 3 - Keras - Tutorial - Happy House
  • 4 - Residual Networks
  • 5 - Object detection - Car detection for Autonomous Driving - YOLO
  • 6 - Art generation with Neural Style Transfer
  • 7 - Face Recognition for the Happy House - Inception Model

• Part 4: Sequence Models

  • 1 - Building a Recurrent Neural Network - Step by Step
  • 2 - Character level language model - Dinosaurus land
  • 3 - Jazz improvisation with LSTM
  • 4 - Word Embeddings - Operations on word vectors and Debiasing
  • 5 - Natural Language Processing - Emojify
  • 6 - Neural Machine Translation with Attention
  • 7 - Speech Recognition Application - Trigger word detection

Featured Projects

Car detection for Autonomous Driving - YOLO

Art generation with Neural Style Transfer

Face Recognition for the Happy House - Inception Model

Residual Networks

Jazz improvisation with LSTM

Natural Language Processing - Emojify

Neural Machine Translation with Attention

Speech Recognition Application - Trigger word detection

第一门课的最后一个练习与第二门课的最后一个练习作对比