| 01 - Continue your practice of grounding techniques for LLMs.mp4 | 1.4 MB | ||
| 01 - Continue your practice of grounding techniques for LLMs.srt | 1 KB | ||
| 01 - Creating LLM evaluation pipelines.mp4 | 8.5 MB | ||
| 01 - Creating LLM evaluation pipelines.srt | 10.1 KB | ||
| 01 - Few-shot learning.mp4 | 5.1 MB | ||
| 01 - Few-shot learning.srt | 4.9 KB | ||
| 01 - Ragas Evaluation paper.mp4 | 9.2 MB | ||
| 01 - Ragas Evaluation paper.srt | 5.5 KB | ||
| 01 - Training LLMs on time-sensitive data.mp4 | 4.4 MB | ||
| 01 - Training LLMs on time-sensitive data.srt | 3.2 KB | ||
| 01 - Understanding grounding techniques for LLMs.mp4 | 2.5 MB | ||
| 01 - Understanding grounding techniques for LLMs.srt | 1.2 KB | ||
| 01 - What is a hallucination.mp4 | 1.7 MB | ||
| 01 - What is a hallucination.srt | 1.3 KB | ||
| 02 - Chain of thought reasoning.mp4 | 7.5 MB | ||
| 02 - Chain of thought reasoning.srt | 5.8 KB | ||
| 02 - Hallucination examples.mp4 | 1.9 MB | ||
| 02 - Hallucination examples.srt | 1.5 KB | ||
| 02 - Hallucinations in large multilingual translation models.mp4 | 15.3 MB | ||
| 02 - Hallucinations in large multilingual translation models.srt | 8.2 KB | ||
| 02 - LLM self-assessment pipelines.mp4 | 19.9 MB | ||
| 02 - LLM self-assessment pipelines.srt | 12.7 KB | ||
| 02 - Poorly curated training data.mp4 | 6.4 MB | ||
| 02 - Poorly curated training data.srt | 3.5 KB | ||
| 02 - Setting up your LLM environment.mp4 | 14.5 MB | ||
| 02 - Setting up your LLM environment.srt | 11.2 KB | ||
| 03 - Comparing hallucinations across LLMs.mp4 | 7.9 MB | ||
| 03 - Comparing hallucinations across LLMs.srt | 5.4 KB | ||
| 03 - Do LLMs know what they don’t know.mp4 | 10.3 MB | ||
| 03 - Do LLMs know what they don’t know.srt | 5.2 KB | ||
| 03 - Faithfulness and context.mp4 | 9.4 MB | ||
| 03 - Faithfulness and context.srt | 6.9 KB | ||
| 03 - Human-in-the-loop systems.mp4 | 15.1 MB | ||
| 03 - Human-in-the-loop systems.srt | 9.5 KB | ||
| 03 - Structured templates.mp4 | 4.4 MB | ||
| 03 - Structured templates.srt | 3.6 KB | ||
| 04 - Ambiguous responses.mp4 | 5.6 MB | ||
| 04 - Ambiguous responses.srt | 3.7 KB | ||
| 04 - Dangers of hallucinations.mp4 | 7 MB | ||
| 04 - Dangers of hallucinations.srt | 5.4 KB | ||
| 04 - Retrieval-augmented generation.mp4 | 6.9 MB | ||
| 04 - Retrieval-augmented generation.srt | 6 KB | ||
| 04 - Set the Clock LLM temporal fine-tuning.mp4 | 8.8 MB | ||
| 04 - Set the Clock LLM temporal fine-tuning.srt | 5.5 KB | ||
| 04 - Specialized models for hallucination detection.mp4 | 24.4 MB | ||
| 04 - Specialized models for hallucination detection.srt | 15.9 KB | ||
| 05 - Building an evaluation dataset.mp4 | 12.8 MB | ||
| 05 - Building an evaluation dataset.srt | 8.5 KB | ||
| 05 - Challenge Finding a hallucination.mp4 | 893.5 KB | ||
| 05 - Challenge Finding a hallucination.srt | 819.2 B | ||
| 05 - Incorrect output structure.mp4 | 5.2 MB | ||
| 05 - Incorrect output structure.srt | 5.2 KB | ||
| 05 - Review of hallucination papers.mp4 | 8.9 MB | ||
| 05 - Review of hallucination papers.srt | 6.2 KB | ||
| 05 - Updating LLM model versions.mp4 | 10.1 MB | ||
| 05 - Updating LLM model versions.srt | 7.2 KB | ||
| 06 - Declining to respond.mp4 | 10.4 MB | ||
| 06 - Declining to respond.srt | 7.4 KB | ||
| 06 - Model fine-tuning for mitigating hallucinations.mp4 | 24.2 MB | ||
| 06 - Model fine-tuning for mitigating hallucinations.srt | 13.7 KB | ||
| 06 - Optimizing prompts with DSPY.mp4 | 48.7 MB | ||
| 06 - Optimizing prompts with DSPY.srt | 27.3 KB | ||
| 06 - Solution Finding a hallucination.mp4 | 6.2 MB | ||
| 06 - Solution Finding a hallucination.srt | 4.6 KB | ||
| 07 - Fine-tuning hallucinations.mp4 | 8.2 MB | ||
| 07 - Fine-tuning hallucinations.srt | 6.1 KB | ||
| 07 - Optimizing hallucination detections with DSPY.mp4 | 19.3 MB | ||
| 07 - Optimizing hallucination detections with DSPY.srt | 10.8 KB | ||
| 07 - Orchestrating workflows through model routing.mp4 | 18.3 MB | ||
| 07 - Orchestrating workflows through model routing.srt | 14.2 KB | ||
| 08 - Challenge Automating ecommerce reviews with LLMs.mp4 | 3.3 MB | ||
| 08 - Challenge Automating ecommerce reviews with LLMs.srt | 2.2 KB | ||
| 08 - LLM sampling techniques and adjustments.mp4 | 10.8 MB | ||
| 08 - LLM sampling techniques and adjustments.srt | 7.1 KB | ||
| 08 - Real-world LLM user testing.mp4 | 16.5 MB | ||
| 08 - Real-world LLM user testing.srt | 11.1 KB | ||
| 09 - Bad citations.mp4 | 4.3 MB | ||
| 09 - Bad citations.srt | 3.2 KB | ||
| 09 - Challenge A more well-rounded AI trivia agent.mp4 | 1.4 MB | ||
| 09 - Challenge A more well-rounded AI trivia agent.srt | 1.2 KB | ||
| 09 - Solution Automating ecommerce reviews with LLMs.mp4 | 8.9 MB | ||
| 09 - Solution Automating ecommerce reviews with LLMs.srt | 4.6 KB | ||
| 10 - Incomplete information extraction.mp4 | 8.2 MB | ||
| 10 - Incomplete information extraction.srt | 5.9 KB | ||
| 10 - Solution A more well-rounded AI trivia agent.mp4 | 8.4 MB | ||
| 10 - Solution A more well-rounded AI trivia agent.srt | 5.4 KB | ||
| Bonus Resources.txt | 409.6 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 88 total files | |||
Grounding Techniques for LLMs
https://FreeCourseWeb.com
Released 8/2024
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Intermediate | Genre: eLearning | Language: English + srt | Duration: 2h 44m | Size: 433 MB
Are you looking to learn more about large language models (LLMs)? Join instructor Denys Linkov as he explores hallucinations, their causes, the implications they have on the reliability and usability of LLMs, and how to mitigate structural and contextual inaccuracies to ensure high-quality, time-sensitive output. Develop practical techniques for addressing hallucinations, including few-shot learning, model fine-tuning, and templates for guiding LLM outputs. You'll also delve into more advanced topics like the chain of thought reasoning, retrieval-augmented generation, and model routing to enhance LLM performance. Test out your new skills along the way with real-world challenges that provide hands-on experience to solidify your learning. Whether you’re an AI researcher, a data scientist, or a tech enthusiast intrigued by the evolving capabilities of LLMs, this course offers valuable insights on navigating the complexities of AI with ease.
This course is integrated with GitHub Codespaces, an instant cloud developer environment that offers all the functionality of your favorite IDE without the need for any local machine setup. With GitHub Codespaces, you can get hands-on practice from any machine, at any time-all while using a tool that you'll likely encounter in the workplace. Check out the "Using GitHub Codespaces with this course" video to learn how to get started.
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