[Coursera] CONVOLUTIONAL NEURAL NETWORKS

By Course Club Last updated Jan 16, 2019

Convolutional Neural Networks

About this Course

This course will teach you how to build convolutional neural networks and apply it to image data. Thanks to deep learning, computer vision is working far better than just two years ago, and this is enabling numerous exciting applications ranging from safe autonomous driving, to accurate face recognition, to automatic reading of radiology images. You will: – Understand how to build a convolutional neural network, including recent variations such as residual networks. – Know how to apply convolutional networks to visual detection and recognition tasks. – Know to use neural style transfer to generate art. – Be able to apply these algorithms to a variety of image, video, and other 2D or 3D data. This is the fourth course of the Deep Learning Specialization.

Syllabus – What you will learn from this course

WEEK

6 hours to complete

Foundations of Convolutional Neural Networks

Learn to implement the foundational layers of CNNs (pooling, convolutions) and to stack them properly in a deep network to solve multi-class image classification problems.

WEEK

5 hours to complete

Deep convolutional models: case studies

Learn about the practical tricks and methods used in deep CNNs straight from the research papers.

WEEK

4 hours to complete

Object detection

Learn how to apply your knowledge of CNNs to one of the toughest but hottest field of computer vision: Object detection.

WEEK

5 hours to complete

Special applications: Face recognition & Neural style transfer

Discover how CNNs can be applied to multiple fields, including art generation and face recognition. Implement your own algorithm to generate art and recognize faces!

About the Deep Learning Specialization

If you want to break into AI, this Specialization will help you do so. Deep Learning is one of the most highly sought after skills in tech. We will help you become good at Deep Learning. In five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. You will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing. You will master not only the theory, but also see how it is applied in industry. You will practice all these ideas in Python and in TensorFlow, which we will teach. You will also hear from many top leaders in Deep Learning, who will share with you their personal stories and give you career advice. AI is transforming multiple industries. After finishing this specialization, you will likely find creative ways to apply it to your work. We will help you master Deep Learning, understand how to apply it, and build a career in AI.

Size:1.00 GB

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https://www.coursera.org/learn/convolutional-neural-networks.