Deep Learning with Caffe2 Practice Exam

Deep Learning with Caffe2

About Deep Learning with Caffe2

A deep learning framework called Caffe was first created at the University of California, Berkeley. It is BSD-licensed and open-source. It has a Python interface and is developed in C++.

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

Why is Deep Learning with Caffe2 important?

Caffe2 is primarily intended for industrial use. It is designed for applications needing extensive object detection and picture categorization. Scalable systems and cross-platform support are its key focuses.

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

Who should take the Deep Learning with Caffe2 Exam?

• Managers
• Data scientists 
• Machine learning enthusiasts
• Staff Software Engineer

Knowledge and Skills required for the Deep Learning with Caffe2

Candidates gain quick success in career of deep learning with caffe2 if they have skills of critical thinking and good communication skills.

Deep Learning with Caffe2 Practice Exam Objectives

Deep Learning with Caffe2 exam focuses on assessing your skills and knowledge in machine learning, deep learning and Caffe2.

Deep Learning with Caffe2 Practice Exam Pre-requisite

There are no prerequisites for the Deep Learning with Caffe2 exam. Candidates who are well versed  in machine learning, deep learning and Caffe2 can easily clear the exam.

Deep Learning with Caffe2 Certification Course Outline

1. Why Deep Learning?
2. Machine Learning Categories
3. Install and Set Up Caffe2
4. Introduce Workspace, Operators, and Nets
5. Housing Price Prediction
6. Training a Linear Regression Model
7. What Is Supervised Learning?
8. Fine-Tune a Model for Recognizing Fashion Products
9. What Are RNNs and LSTMs?
10. Why Deep Reinforcement Learning?
11. What Is Deep Reinforcement Learning?
12. AI on Mobile Devices Using Face ID
13. Set Up Caffe2 on Linux
14. Understanding the Caffe2 Architecture
15. Transitioning from Machine Learning to Deep Learning
16. Running an Image Classifier Using Caffe2
17. Learn about Matrices Using Python – NumPy
18. Understanding and Implementing Logistic Regression and Neural Networks
19. Understanding and Implementing Deep Neural Networks
20. Caffe2 Introduction

Exam Format and Information

Certification name – Certificate in Deep Learning with 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