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
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).
There are 4 parts in this repository:
Part 1: Basis of Neural Networks and Deep Learning
Part 2: Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
Part 3: Convolutional Neural Networks
Part 4: Sequence Models
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