Bias And Fairness In Large Language Models

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  • Type Tutorials
  • Language English
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Bias And Fairness In Large Language Models

https://CourseWikia.com

Published 4/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.29 GB | Duration: 0h 43m

Explore Potential Biases in (AI) Training Data and Strategies to Develop Fair and Unbiased Large Language Models

What you'll learn
Introduction To Bias And Fairness In Large Language Models
Types Of Biases In Training Data
Case Studies On Bias In Language Models
Measuring Bias In Language Models
Strategies To Mitigate Bias In Language Models
Ethical Considerations In Developing ChatGPT-Like Models

Requirements
Here are the requirements and prerequisites for the "Bias and Fairness in Large Language Models" Udemy course: Prerequisites: No prior experience with large language models or AI ethics is required. This course is designed for learners at all levels, from beginners to experienced AI practitioners. A basic understanding of machine learning and natural language processing concepts would be helpful, but not strictly necessary. The course will provide explanations and introductions to these topics as needed. Familiarity with using online tools and platforms for learning and research purposes.

Files:

[ CourseWikia.com ] Bias And Fairness In Large Language Models
  • Get Bonus Downloads Here.url (0.2 KB)
  • ~Get Your Files Here ! 1 - Introduction
    • 1 - Intro Video.mp4 (24.4 MB)
    • 2 - The Rise of Large Language Models.mp4 (27.7 MB)
    • 3 - The Importance of Bias and Fairness.mp4 (22.4 MB)
    • 4 - Course Objectives and Overview.mp4 (38.8 MB)
    2 - Module 1 Understanding Bias in LLMs
    • 5 - Defining Bias in LLMs.mp4 (28.4 MB)
    • 6 - Types of Bias in LLMs.mp4 (168.5 MB)
    • 7 - Impacts of Biased LLM Outputs.mp4 (125.2 MB)
    3 - Module 2 Mitigating Bias in LLM Training
    • 10 - Illustrating Debiasing Techniques 1.mp4 (50.1 MB)
    • 11 - Illustrating Debiasing Techniques 2.mp4 (39.7 MB)
    • 8 - Debiasing Techniques.mp4 (138.0 MB)
    • 9 - Algorithmic Approaches.mp4 (68.9 MB)
    4 - Module 3 Evaluating Bias and Fairness
    • 12 - Measuring Bias and Fairness.mp4 (60.3 MB)
    • 13 - Challenges and Considerations.mp4 (130.4 MB)
    • 14 - Transitioning to Realworld Considerations.mp4 (17.5 MB)
    5 - Module 4 Realworld Considerations
    • 15 - Balancing Fairness and Other Attributes.mp4 (100.8 MB)
    • 16 - Deployment and Monitoring.mp4 (74.6 MB)
    • 17 - Interdisciplinary Collaboration.mp4 (83.1 MB)
    6 - Conclusion
    • 18 - Key Takeaways.mp4 (51.5 MB)
    • 19 - Future Directions and Resources.mp4 (72.7 MB)
    • Bonus Resources.txt (0.4 KB)

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