About this video

Caffe is a popular Deep Learning library implemented in C++ and renowned for its speed and efficiency. This video course is for you if you are familiar with C++ and want to get started with Deep Learning using Caffe to train real-world models.

This course will teach you how Deep Learning functions and how the Caffe framework enhances the speed and performance of your model to make it smarter for real-world uses. You will learn practical skills about creating layers, configuring networks, training and deploying using Caffe (written in C++). You will also learn about some of the internals of Caffe. Throughout the course, you will work with practical examples to get a good training in Deep Learning.

By the end of this course, you will have the skills to build and train your own real-world Deep Learning models using Caffe.

The code bundle for this video course is available at - https://github.com/PacktPublishing/C-Deep-Learning-with-Caffe

Style and Approach

The course has been organized into layers. We start at the surface and keep digging deeper as we proceed. We adopt a practical approach, whereby you learn a concept and then put it into practice like “Peek under the Hood” for programmers who are familiar with C++. We also help you avoid common pitfalls most people encounter in Caffe

Publication date:
December 2018
1 hours 38 minutes

About the Author

  • Aman Angrish

    Aman Angrish is a programmer and entrepreneur with nearly 19 years' experience in the software industry. He is the creator of ThatNeedle technology (a proprietary fast Natural Language Processing stack) and has applied for patent. His work includes Natural Language Processing, Natural language understanding, Semantic search, chatbots, and voice-based searches. He is working to expand the cutting edge of technology to make it deeper and faster. He is an NTSE Scholar and a graduate from PEC (Punjab Engineering College), Chandigarh, India.

    Browse publications by this author

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