PyTorch is fast emerging as a popular choice for building deep learning models owing to its flexibility, ease-of-use, and built-in support for optimized hardware such as GPUs. Using PyTorch, you can build complex deep learning models, while still using Python-native support for debugging and visualization. In this course, Building Your First PyTorch Solution, you will gain the ability to get up and running by building your first regression and classification models. First, you will learn how to install PyTorch using pip and conda, and see how to leverage GPU support. Next, you will discover how to hand-craft a linear regression model using a single neuron, by defining the loss function yourself. You will then see how PyTorch optimizers can be used to make this process a lot more seamless. You will understand how different activation functions and dropout can be added to PyTorch neural networks. Finally, you will explore how to build classification models in PyTorch. You will round out the course by extending the PyTorch base module to implement a custom classifier. When you’re finished with this course, you will have the skills and knowledge to move on to installing PyTorch from scratch in a new environment and building models leveraging and customizing various PyTorch abstractions.
Author Name: Janani Ravi
Author Description:
Janani has a Masters degree from Stanford and worked for 7+ years at Google. She was one of the original engineers on Google Docs and holds 4 patents for its real-time collaborative editing framework. After spending years working in tech in the Bay Area, New York, and Singapore at companies such as Microsoft, Google, and Flipkart, Janani finally decided to combine her love for technology with her passion for teaching. She is now the co-founder of Loonycorn, a content studio focused on providing … more

Table of Contents

• Course Overview
  1min
• Installing PyTorch on a Local Machine
  37mins
• Understanding Linear Regression with a Single Neuron
  34mins
• Building a Regression Model Using PyTorch
  37mins
• Building a Classification Model Using PyTorch
  33mins