Deep learning specialization
Deep_Learning_Specialization by DeepLearning.ai on Coursera
IMPORTANT:Before accessing this repo, be sure to abide by the honest code of coursera which means you are not using this repo code to submit as your own to pass the lab assignments. This repo is only for information purpose or audience who audit this course on coursera. All notenooks and lecture notes are property of deeplearning and may be deleted if objected.
Master Deep Learning, and Break into AI
Organization: deeplearning.ai
Coursera: Deep Learning Specialization
Instructor: Andrew Ng
Introduction
This repo contains all the lab assignments as well as lecture slides for deep learning specialization by deeplearning.ai on coursera. All the code base and images, are taken from Deep Learning Specialization on Coursera
You will master the fundamentals of Deep Learning, how to create neural networks, and how to lead successful machine learning projects in five courses. Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and other topics will be covered. You will work on healthcare, autonomous driving, sign language reading, music generation, and natural language processing case studies. You will not only learn the theory, but you will also see how it is utilised in industry. All of these concepts will be practised in Python and TensorFlow.
