Practice Exam
Certificate in Caffe2

Certificate in Caffe2

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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

 

  1. Deep Learning
  2. Why Caffe2?
  3. Supervised Learning
  4. Transfer Learning
  5. Set Up Caffe2 on Linux
  6. Understanding the Caffe2 Architecture
  7. Caffe2 Introduction
  8. Caffe2 Python Wrapper
  9. Mathematical Operators in Caffe2
  10. Network Creators and Assisters in Caffe2
  11. Pooling Layer and Dropout in Caffe2
  12. Role of Activation Functions in Solving Non-Linear Optimization
  13. Machine Learning Strategy
  14. Optimizing Neural Networks
  15. Optimization Algorithms
  16. Introduction to Recurrent Neural Networks

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