Caffe2 Practice Exam

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.

Caffe2 has gained immense popularity across the globe resulting in huge demand for certified professionals.

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.

Caffe2 certified professionals, executives and managers are in high demand in companies across the globe.

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

Knowledge and Skills required for the Caffe2

Specific skills are needed to excel in career of Caffe2 which includes analytical bent of mind and quick learning skills.

Caffe2 Practice Exam Objectives

Caffe2 exam focuses on assessing your skills and knowledge in Caffe2

Caffe2 Practice Exam Pre-requisite

There are no prerequisites for the Caffe2 exam. Candidates who are well versed  in Caffe2 can easily clear the exam.

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

Exam Format and Information

Certification name – Certificate in Caffe2
Exam duration – 60 minutes
Exam type - Multiple Choice Questions
Eligibility / pre-requisite - None
Exam language - English
Exam format - Online
Passing score - 25
Exam Fees  - INR 1199