Deep Neural Networks with PyTorch

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.

Career Relevance by Data Role

The techniques and tools covered in Deep Neural Networks with PyTorch are most similar to the requirements found in Data Scientist job advertisements.

Similarity Scores (Out of 100)

Fast Facts

PyTorch Python

Classification Data Sets Deep Learning Functions Regression Machine Learning Neural Networks

Similar Opportunities
Introduction to Deep Learning

Coursera - National Research University Higher School of Economics