Computer Vision for Industrial Inspection Training
Course Authors
Computer Vision for Industrial Inspection Training Hands-on (Online, Onsite, and Classroom Live)
| Commitment | 1 Day, 7-8 hours a day. |
| Language | English |
| User Ratings | Average User Rating 4.8 See what learners said |
| Price | REQUEST |
| Delivery Options | Instructor-Led Onsite, Online, and Classroom Live |
COURSE OVERVIEW
In this Computer Vision for Industrial Inspection Training workshop, you’ll learn how to quickly develop and deploy a machine learning model that uses deep learning for computer vision to perform defect classification and other visual recognition tasks. Using NVIDIA’s real production dataset, this workshop illustrates how the solution can be easily applied to various manufacturing and industrial inspection use cases.
This course is part of the following Certifications:
- NVIDIA-Certified Associate: Generative AI Multimodal
Please note that once a booking has been confirmed, it is non-refundable. This means that after you have confirmed your seat for an event, it cannot be canceled, and no refund will be issued, regardless of attendance.
WHAT'S INCLUDED?
- 1 day of Computer Vision for Industrial Inspection Training with an expert instructor
- Computer Vision for Industrial Inspection Electronic Course Guide
- Certificate of Completion
- 100% Satisfaction Guarantee
RESOURCES
- Computer Vision for Industrial Inspection – https://www.wiley.com/
- Computer Vision for Industrial Inspection – https://www.packtpub.com/
- Computer Vision for Industrial Inspection – https://store.logicaloperations.com/
- Computer Vision for Industrial Inspection – https://us.artechhouse.com/
- Computer Vision for Industrial Inspection Training – https://www.amazon.com/
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ADDITIONAL INFORMATION
COURSE OBJECTIVES
Upon completion of this Computer Vision for Industrial Inspection Training course, participants can:
- Extract meaningful insights from the provided data set using Pandas DataFrame.
- Apply transfer-learning to a deep learning classification model.
- Fine-tune the deep learning model and set up evaluation metrics.
- Deploy and measure model performance.
- Experiment with various inference configurations to optimize model performance.
CUSTOMIZE IT
- We can adapt this Computer Vision for Industrial Inspection Training course to your group’s background and work requirements at little to no added cost.
- If you are familiar with some aspects of this Computer Vision for Industrial Inspection course, we can omit or shorten their discussion.
- We can adjust the emphasis placed on the various topics or build the Computer Vision for Industrial Inspection course around the mix of technologies of interest to you (including technologies other than those in this outline).
- If your background is nontechnical, we can exclude the more technical topics, include the topics that may be of special interest to you (e.g., as a manager or policymaker), and present the Computer Vision for Industrial Inspection course in a manner understandable to lay audiences.
AUDIENCE/TARGET GROUP
The target audience for this Computer Vision for Industrial Inspection Training course:
- ALL
CLASS PREREQUISITES
The knowledge and skills that a learner must have before attending this Computer Vision for Industrial Inspection Training course are:
- Experience with Python; basic understanding of data processing and deep learning.
- To gain experience with Python, we suggest this Python tutorial.
- To get a basic understanding of data processing and deep learning, we suggest DLI’s Fundamentals of Deep Learning.
COURSE SYLLABUS
Introduction
- Meet the instructor.
- Create an account at courses.nvidia.com/join
Data Exploration and Pre-Processing with DALI
- Learn how to extract valuable insights from a data set and pre-process image data for deep learning model consumption.
- Explore data set with Pandas
- Pre-process data with DALI
- Assess scope for feasibility testing
Efficient Model Training with TAO Toolkit
- Learn how to efficiently train a classification model for the purpose of defect detection using transfer learning techniques
- Train a deep learning model with TAO Toolkit
- Evaluate the accuracy of the model
- Iterate model training to improve accuracy
Model Deployment for Inference
- Learn how to deploy and measure the performance of a deep learning model
- Optimize deep learning models with TensorRT
- Deploy model with Triton Inference Server
- Explore and assess the impact of various inference configurations
Assessment and Q&A
