Course Overview
In this 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 own real production dataset as an example, this workshop illustrates how the solution can be easily applied to a variety of manufacturing and industrial inspection use cases.
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 cancelled and no refund will be issued, regardless of attendance.
Certifications
This course is part of the following Certifications:
Prerequisites
- 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 Objectives
- 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.