Learn how to create state of the art neural networks for deep learning with Facebook’s PyTorch Deep Learning library.
What you’ll learn
- Learn how to use NumPy to format data into arrays
- Use pandas for data manipulation and cleaning
- Learn classic machine learning theory principals
- Use PyTorch Deep Learning Library for image classification
- Be able to work through basic derivative calculations
- Admin Permissions on your computer (ability to download our files)
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!
In this course we will teach you everything you need to know to get started with Deep Learning with Pytorch, including:
- Machine Learning Theory
- Test/Train/Validation Data Splits
- Model Evaluation – Regression and Classification Tasks
- Unsupervised Learning Tasks
- Tensors with PyTorch
- Neural Network Theory
Who this course is for:
- Intermediate to Advanced Python Developers wanting to learn about Deep Learning with PyTorch