Caffe2
About Caffe2
Caffe is the name of a deep learning framework that was created at the University of California, Berkeley. Under a BSD license, it is open source. With a Python user interface, it is written in C++.
Caffe2 is primarily designed with production in mind. It is intended for use in applications that need object identification and large-scale picture categorization. Scalable systems and cross-platform compatibility are its key points of emphasis.
Why is Caffe2 important?
With Caffe2, you can scale up or down extremely rapidly without reworking your design. When compared to a single GPU training, Caffe2 offers deep learning training that scales almost linearly and up to 7.7x faster with 8 GPUs.
Who should take the Caffe2 Exam?
- This is for data scientists and machine learning enthusiasts who are eager to understand the Caffe 2 framework for deep learning model training, creating practical applications, and creating production-grade services and modules to automate practical situations.
- Machine learning, AI managers, senior engineers
Caffe2 Certification Course Outline
- Deep Learning
- Why Caffe2?
- Supervised Learning
- Transfer Learning
- Set Up Caffe2 on Linux
- Understanding the Caffe2 Architecture
- Caffe2 Introduction
- Caffe2 Python Wrapper
- Mathematical Operators in Caffe2
- Network Creators and Assisters in Caffe2
- Pooling Layer and Dropout in Caffe2
- Role of Activation Functions in Solving Non-Linear Optimization
- Machine Learning Strategy
- Optimizing Neural Networks
- Optimization Algorithms
- Introduction to Recurrent Neural Networks