Applying Hugging Face Machine Learning Pipelines in Python - Learn Interactively

Description

In this course, you will :

• Explore the Hugging Face artificial intelligence library, paying special attention to natural language processing (NLP) and computer vision. You'll start by learning about Hugging Face's approach to deep learning, with a focus on transformers.
• Discover Hugging Face's pipeline API model and apply it to various NLP tasks like classification, summarization, question answering, and more.
• You will then proceed with a new set of Hugging Face pipelines for computer vision tasks such as object detection and segmentation.
• A familiarity with Hugging Face and their library of machine learning models
• A working knowledge of Hugging Face’s pipeline APIs and their applications
• The ability to apply Hugging Face models to generate and read text using natural language processing
• The ability to apply Hugging Face models to computer vision tasks
• Hands-on experience implementing Hugging Face models using Python and PyTorch

Syllabus :

1. Introduction

• Introduction to the Course
• Hugging Face

 

2. NLP

• Introduction to NLP Inference
• Text and Token Classification
• Text Summarization
• Machine Translation
• Question Answering
• Text GenerationSimilarity
• Fill Mask

\3. Computer Vision

• Image Classification
• Object Detection
• Segmentation

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