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DeepNeural Networks with PyTorch

DeepNeural Networks with PyTorch

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

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Course Highlights

  • Start instantly and learn at your own schedule.

  • Earn a certificate of learning on course completion 

  • This course is offered by IBM

Duration: 49 Days

Mode of learning: Online self study

Course Overview

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.

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