About this video
Deep learning is one of the most highly sought-after skills in the technology sector. If you want to take a crack at AI, then this course will help you do so. One of the many reasons for choosing Caffe2 for this course is its processing speed as compared to other platforms. Since the basis of the architecture in Caffe2 is CUDA, it provides flexibility in optimizing the code as per the hardware being used.
You’ll learn the foundations of Deep Learning, understand how to build neural networks and develop an understanding of convolutional networks, RNNs, Adam, Dropout, BatchNorm and more. You’ll be working on various projects throughout this MOOC with a focus on how to train and manipulate a deep neural network effectively. You’ll practice all these ideas in Caffe2 using Python programming languages.
By the end of the course, you’ll gain an understanding of every element of Caffe2 and be able to use the library in the most efficient way.
All the code and supporting files for this course are available on Github at https://github.com/PacktPublishing/Introduction-to-Deep-Learning-with-Caffe2
Style and Approach
An exhaustive course packed with step-by-step instructions, working examples, and actionable advice on understanding Caffe2 to build deep learning applications. This course is properly segmented so that you can learn at your own pace and focus on your area of interest.
- Publication date:
- August 2018
- 1 hour 56 minutes