- Caffe2 Tutorial
- Caffe2 - Home
- Caffe2 - Introduction
- Caffe2 - Overview
- Caffe2 - Installation
- Verifying Access to Pre-Trained Models
- Image Classification Using Pre-Trained Model
- Caffe2 - Creating Your Own Network
- Caffe2 - Defining Complex Networks
- Caffe2 Useful Resources
- Caffe2 - Quick Guide
- Caffe2 - Useful Resources
- Caffe2 - Discussion
- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
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Caffe2 Tutorial
In this tutorial, we will learn how to use a deep learning framework named Caffe2 (Convolutional Architecture for Fast Feature Embedding). Moreover, we will understand the difference between traditional machine learning and deep learning, what are the new features in Caffe2 as compared to Caffe and the installation instructions for Caffe2.
Audience
This tutorial is designed for those who have keen interest in learning about creating models and new algorithms for solving problems with the help of a modular and scalable deep learning framework, Caffe2. Furthermore, it is for the programmers who are eager to bring their creations to scale with the help of graphics processing units (GPUs) in the cloud or to common people on mobile with cross - platform libraries.
Prerequisites
Before you proceed with this tutorial, we assume that you have prior knowledge about deep learning framework, machine learning library PyTorch and programming languages such as C++, Python and MATLAB. If you are novice to any of the technologies mentioned before, you can refer to the respective tutorials before beginning with this tutorial.