What you will learn

• Understanding transformers and their role in NLP
• Hands-on experience with Hugging Face Transformers
• Familiarity with data sets and related evaluation criteria
• Fine tuning transformers for text classification, question and answer, natural language inference, text summarization and machine translation.
• Understanding the principles of transformer fine tuning
• Applying transformer fine-tuning to real NLP problems
• Familiarity with different types of transformers such as BERT, GPT-2 and T5
• Hands-on experience with the Hugging Face Transformers library

This course is suitable for people who

• NLP Professionals: This course is designed for NLP professionals who want to learn how to fine-tune pre-trained transformer models to achieve superior results in a wide range of NLP tasks.
• Researchers: This course is also designed for researchers interested in exploring the potential of transformer fine-tuning for new NLP applications.
• Students: This course is suitable for students who have taken an introductory NLP course and want to deepen their understanding of transformer models and their application to real-world NLP problems.
• Developers: This course is useful for developers who want to incorporate transformer fine-tuning into their NLP applications.
• Enthusiasts: This course is accessible to enthusiasts who are interested in learning about transformer fine tuning and applying it to personal projects.

Installation guide

After Extract, view with your favorite Player.

Subtitle: English

Quality: 720p

Changes:

Version 2024/8 has increased the number of 40 lessons and the duration of 4 hours and 16 minutes compared to 2024/6. English subtitles have also been added to the course.

The 2024/12 version has increased the duration by 5 minutes compared to the 2024/8 version.