Hugging Face Integration: Leveraging Pre-trained Models

This module focuses on integrating state-of-the-art machine learning models from Hugging Face into manufacturing applications and workflows. You will learn how to utilize Hugging Face Transformers, Datasets, and Accelerate libraries to fine-tune and deploy pre-trained models for tasks such as natural language processing (NLP) for quality control, computer vision for automated inspection, and time-series analysis for predictive maintenance.

Key Learning Outcomes:

Module Sections:

1. Introduction to Hugging Face Ecosystem

Explore the core libraries and concepts of Hugging Face, and how they enable rapid development and deployment of AI models.

2. NLP for Manufacturing: Text Analysis & Quality Control

Utilize pre-trained NLP models for sentiment analysis of customer feedback, classification of defect reports, and extraction of key information from unstructured text data.

3. Computer Vision for Automated Inspection

Apply image classification, object detection, and segmentation models for automated visual inspection of products, anomaly detection, and quality assurance.

4. Time-Series Analysis for Predictive Maintenance

Leverage Hugging Face models for analyzing sensor data, predicting equipment failures, and optimizing maintenance schedules in manufacturing.

5. Deployment & Monitoring of Hugging Face Models

Learn how to deploy Hugging Face models to production, monitor their performance, and update them as new data becomes available.