Bias And Fairness In Large Language Models

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Bias And Fairness In Large Language Models (Size: 1.3 GB)
  1 - Intro Video.mp4 24.4 MB
  10 - Illustrating Debiasing Techniques 1.mp4 50.1 MB
  11 - Illustrating Debiasing Techniques 2.mp4 39.7 MB
  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
  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
  18 - Key Takeaways.mp4 51.5 MB
  19 - Future Directions and Resources.mp4 72.7 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
  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
  8 - Debiasing Techniques.mp4 138 MB
  9 - Algorithmic Approaches.mp4 68.9 MB
  Bonus Resources.txt 409.6 B
  Get Bonus Downloads Here.url 204.8 B
  ▲ 21 total files

Description


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.

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