IBM - DeepNeural Networks with PyTorch

Offered byCoursera

DeepNeural Networks with PyTorch
at
Coursera
Overview

Upskilling is a better roadmap to success. Enroll in this course to learn critical principles of Data Science through real-life case studies & examples

Duration	31 hours
Total fee	Free
Mode of learning	Online
Difficulty level	Intermediate
Official Website	Explore Free Course
Credential	Certificate

DeepNeural Networks with PyTorch
at
Coursera
Highlights

Start instantly and learn at your own schedule.
Earn a certificate of learning on course completion
A great course for learning Data Science
This course is offered by IBM

DeepNeural Networks with PyTorch
at
Coursera
Course details

Skills you will learn

Python Data Science

What are the course deliverables?

Explain and apply their knowledge of Deep Neural Networks and related machine learning methods
Know how to use Python libraries such as PyTorch for Deep Learning applications
Build Deep Neural Networks using PyTorch

More about this course

The course will teach you how to develop deep learning models using Pytorch. The course will start with Pytorch's tensors and Automatic differentiation package. Then each section will cover different models starting off with fundamentals such as Linear Regression, and logistic/softmax regression. Followed by Feedforward deep neural networks, the role of different activation functions, normalization and dropout layers. Then Convolutional Neural Networks and Transfer learning will be covered. Finally, several other Deep learning methods will be covered.