This is the code repository for C++ Deep Learning with Caffe [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.
C++ deep larning with Caffe aims to get C++ programmers started with concepts of Deep learning. You will learn what it means to be Deep in the technical sense of the word. You will see how to install Caffe on a fresh Ubuntu from the scratch, run code, inspect and understand the output, look at many important data structures used. You will see how to go through the process of preparing data, training, deploying, testing, fine-tuning etc. You will get clarity on on some common misconceptions about deep learning and components. There are frequent code references as well as conceptual insights that will help you get started with Deep learning with Caffe and enable you to start experimenting on your own!
- Important Deep Learning concepts to get started with
- Introduction to Caffe and its functionalities
- Relating Caffe to Deep Learning concepts
- Elements such as blob, network for model representation in Caffe
- Training neural network with Caffe's C++ API
- Training, tweaking, and deploying Caffe as per your requirements
- Avoiding common practical mistakes and pitfalls
To fully benefit from the coverage included in this course, you will need:
To fully benefit from the coverage included in this course, you will need:
● Prior working knowledge of the C++ language (including templates)
● Working knowledge of Linux
● Working knowledge of vi editor
This course has the following software requirements:
This course has the following software requirements:
This course has been tested on the following system configuration:
● Ubuntu 18, 3gb ram, 1 CPU
Minimum Hardware Requirements:
● The demo will be on an Ubuntu (Linux) computer in the cloud with about 3 GB RAM. You don’t need to own one. You can hire one in the cloud for as little as 3 cents per hour!
Software Requirements:
● We will be starting with a fresh Ubuntu system and installing everything from scratch so you can learn how it’s done. You can connect to a remote Ubuntu with your Mac or Windows using the appropriate remote connetion app like
● Terminal ssh (Mac) or Putty(Windows)