Deep Neural Networks with PyTorch

Deep Neural Networks with PyTorch ranks 6th on the list of best online PyTorch courses. Learn Deep Neural Networks with IBM's PyTorch. The course will teach you how to use Pytorch to create deep learning models. The course will teach you how to use Pytorch to create deep learning models.

The course will begin with tensors and the Automatic differentiation package in Pytorch. You'll start by learning about Linear Regression and logistic/softmax regression. Feedforward deep neural networks, the role of different activation functions, normalization, and dropout layers are then discussed. Finally, this PyTorch course will cover Convolutional Neural Networks and Transfer Learning.

In this course, you will learn how to:

• develop deep learning models using PyTorch.
• start with PyTorch's tensors and Automatic differentiation package.
• use PyTorch for Deep Learning application.
• build Deep Neural Networks using PyTorch.

The course includes:

• Tensor and Datasets
• Linear Regression Pytorch Way
• Multiple Input Output Linear Regression
• Logistic Regression for Classification
• Shallow Neural and Deep Networks
• Convolutional Neural Network

You can take Deep Neural Networks with PyTorch certification course on Coursera.

Course rating: 4.4 out of 5.0
Duration: 31 h
Certificate: Certificate on purchase
Enroll here: coursera.org/learn/deep-neural-networks-with-pytorch