Welcome to the best online course for learning about Deep Learning with Python and PyTorch!

PyTorch is an open source deep learning platform that provides a seamless path from research prototyping to production deployment. It is rapidly becoming one of the most popular deep learning frameworks for Python. Deep integration into Python allows popular libraries and packages to be used for easily writing neural network layers in Python. A rich ecosystem of tools and libraries extends PyTorch and supports development in computer vision, NLP and more.

This course focuses on balancing important theory concepts with practical hands-on exercises and projects that let you learn how to apply the concepts in the course to your own data sets! When you enroll in this course you will get access to carefully laid out notebooks that explain concepts in an easy to understand manner, including both code and explanations side by side. You will also get access to our slides that explain theory through easy to understand visualizations.

In this course we will teach you everything you need to know to get started with Deep Learning with Pytorch, including:

• NumPy

• Pandas

• Machine Learning Theory

• Test/Train/Validation Data Splits

• Model Evaluation - Regression and Classification Tasks

• Unsupervised Learning Tasks

• Tensors with PyTorch

• Neural Network Theory

  • Perceptrons

  • Networks

  • Activation Functions

  • Cost/Loss Functions

  • Backpropagation

  • Gradients

• Artificial Neural Networks

• Convolutional Neural Networks

• Recurrent Neural Networks

• and much more!

By the end of this course you will be able to create a wide variety of deep learning models to solve your own problems with your own data sets.