Practical examples will show you how to code once and run Deep Learning models from anywhere.
About This Video
- Caffe2 is a fast and effective deep learning tool.
- You can easily train your own neural networks
- This guide is concise and easy to follow, with many practical examples.
Caffe2, which is open-sourced by Facebook, provides a flexible, simple framework for efficient deep learning. This course will explain Caffe2 and how to train deep learning models.
The course begins with basic concepts of Caffe2 like workspaces, operators and nets. Next, you will learn how Caffe2's API brew can be used to build a model. Convolutional neural networks (CNNs), which can recognize handwriting and fashion items from images, will be taught. You will learn how to transfer knowledge to allow you work with CNN's image recognition software by fine-tuning models already pre-trained on large-scale datasets. We will cover common models like ResNet-50. The course will also teach you how to deploy your models across any platform.
This course will teach you how to train deep learning models with Caffe2. It provides high-performance, first-class support for distributed training, mobile deployment and flexibility.
All the code files for this course are available on Github at https://github.com/PacktPublishing/Hands-On-Deep-Learning-with-Caffe2
