Learn PyTorch from the very basics to advanced models like Generative Adverserial Networks and Image Captioning
What you’ll learn
A coding-focused introduction to Deep Learning using PyTorch, starting from the very basics and going all the way up to advanced topics like Generative Adverserial Networks
Requirements for PyTorch framework
- Basic knowledge of Python
- Basic linear algebra (vectors, matrices etc.)
Description
“PyTorch: Zero to GANs” is an online course and series of tutorials on building deep learning models with PyTorch, an open source neural networks library. Here are the concepts covered in this course:
- PyTorch Basics: Tensors & Gradients
- Linear Regression & Gradient Descent
- Classification using Logistic Regression
- Feedforward Neural Networks & Training on GPUs (this post)
- Coming soon.. (CNNs, RNNs, transfer learning, GANs etc.)
This course will be updated on a weekly basis with new material.
Who this course is for:
- Students and developers curious about data science
- Data scientists and machine learning engineers curious about PyTorch
About Instructor of this Course
Software Consultant & Entrepreneur
- 4.6 Instructor Rating
- 334 Reviews
- 34,883 Students
- 2 Courses
I’m a Software Consultant and Entrepreneur. I’ve worked extensively on dozens of products and technologies with teams around the world, including Silicon Valley, Japan, Germany, Israel and India. As an entrepreneur I’ve launched multiple products that have gone on to acquire 100s of thousands of users. Teaching is my passion, and I often conduct workshops for emerging technologies I’m interested in. I also like to write blogs and develop open source software in my free time.
Content is From Udemy
Start Learning ______ Deep Learning – Zero to GANs
