At Learnopencv.com, we have adopted a mission of spreading awareness and educate a global workforce on Artificial Intelligence. Taking a step further in that direction, we have started creating tutorials for getting started in Deep Learning with PyTorch. We hope that this will be helpful for people who want to get started in Deep Learning and PyTorch.
1. PyTorch for Beginners
We have created a series of tutorials for absolute beginners to get started with PyTorch and Torchvision. There are lots of tutorials on the PyTorch website and we have tried to write these tutorials in such a way that there is minimum overlap with those tutorials.
Here is a list of tutorials in this series:
1.1. Introduction to PyTorch: Basics
This post is an introduction to PyTorch for those who just know about PyTorch but have never actually used it. We cover the basics of PyTorch Tensors in this tutorial with a few examples. Check out the full tutorial.
1.2. PyTorch for Beginners: Image Classification using Pre-trained models
In this tutorial, we introduce the Torchvision package and discuss how we can use it for Image Classification. We compare different models on the basis of Speed, Accuracy, model size etc, which will help you decide which models to use in your applications. Check out the full tutorial.
1.3. Image Classification using Transfer Learning in PyTorch
In this tutorial, we discuss how to perform Transfer Learning using pre-trained models using PyTorch. We use a subset of the CalTech256 dataset to perform Image Classification to distinguish between 10 different types of animals. Check out the full tutorial.
1.4. PyTorch Model Inference using ONNX and Caffe2
In this tutorial, we look at the deployment pipeline used in PyTorch. We discuss how to convert models trained in PyTorch to a universal format called ONNX. Then we load the model see how to perform inference in Caffe2 ( another Deep Learning library specifically used for deploying deep learning models ). Check out the full tutorial.
1.5. PyTorch for Beginners: Semantic Segmentation using torchvision
In this post, we discuss how to use pre-trained Torchvision models for Semantic Segmentation. The two models that are covered are Fully Convolutional Network and DeepLab v3. Check out the full tutorial.
More tutorials to come…