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Caffe2 Study Notes

In this study notes, we will learn how to utilize a deep learning framework named Caffe2 (Convolutional Architecture for Fast Feature Embedding). Additionally, we will understand the difference between traditional machine learning and deep learning, what are the new highlights in Caffe2 as compared to Caffe and the installation guidelines for Caffe2.


This study notes is designed for those who have keen interest in learning about creating models and new algorithms for solving problems with the assistance of a modular and scalable deep learning framework, Caffe2. Besides, it is for the programmers who are eager to bring their creations to scale with the assistance of graphics processing units (GPUs) in the cloud or to common people on mobile with cross - platform libraries.


Before you continue with this study notes, we expect that you have earlier 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 study notes before starting with this study notes.

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