Linkedin - Prompt Engineering with LangChain

Creation Time	Aug. 2, 2024, 9:56 a.m.
Last Access Time	Nov. 25, 2024, 8:34 p.m.
File Size	1.3 GB
Keywords	Prompt - LangChain Engineering Linkedin with
Total Requests	108
Total Files	48
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4. Components of LangChain/3. Model I O- Interface with language models.mp4 85.2 MB
7. Prompting Techniques/5. RAG.mp4 80.7 MB
4. Components of LangChain/5. Chains- Construct sequences of calls.mp4 74.8 MB
4. Components of LangChain/4. Retrieval- Interface with application-specific data.mp4 58.4 MB
7. Prompting Techniques/7. Plan and execute.mp4 56.8 MB
4. Components of LangChain/6. Agents- Let chains choose tools based on high-level directives.mp4 55.4 MB
7. Prompting Techniques/3. Self-ask.mp4 51.0 MB
7. Prompting Techniques/6. FLARE.mp4 50.5 MB
8. Prompt Management a.k.a. PromptOps/5. LangSmith deep dive.mp4 48.5 MB
8. Prompt Management a.k.a. PromptOps/4. Prompt versioning in LangSmith.mp4 40.7 MB
4. Components of LangChain/7. Memory- Persist application state between runs of a chain.mp4 40.3 MB
7. Prompting Techniques/4. ReAct.mp4 39.7 MB
7. Prompting Techniques/1. Chain of thought.mp4 38.9 MB
3. LLMs and Text Generation/2. Base LLMs vs. instruction-tuned LLMs.mp4 35.0 MB
6. Prompt Templates Deep Dive/10. Few-shot prompt templates.mp4 33.9 MB
8. Prompt Management a.k.a. PromptOps/6. Managing prompt length for agents.mp4 33.0 MB
6. Prompt Templates Deep Dive/6. Custom prompt templates.mp4 31.2 MB
5. Basics of Prompting/2. Principles and tactics for prompting.mp4 30.7 MB
6. Prompt Templates Deep Dive/15. N-gram overlap example selector.mp4 30.1 MB
7. Prompting Techniques/2. Self-consistency.mp4 29.6 MB
6. Prompt Templates Deep Dive/1. Introduction to prompt templates.mp4 26.6 MB
6. Prompt Templates Deep Dive/7. Prompt pipelining.mp4 25.8 MB
8. Prompt Management a.k.a. PromptOps/3. LangSmith walkthrough.mp4 24.4 MB
6. Prompt Templates Deep Dive/11. Few-shot prompt templates for chat.mp4 22.2 MB
6. Prompt Templates Deep Dive/3. Chat prompt template.mp4 21.6 MB
6. Prompt Templates Deep Dive/5. Zero-shot prompts.mp4 21.1 MB
6. Prompt Templates Deep Dive/2. Multi-input prompt templates.mp4 20.4 MB
6. Prompt Templates Deep Dive/9. Prompt composition.mp4 18.0 MB
6. Prompt Templates Deep Dive/14. Max marginal relevance example selector.mp4 17.4 MB
6. Prompt Templates Deep Dive/17. Partial prompt templates.mp4 15.7 MB
6. Prompt Templates Deep Dive/8. Chat prompt pipelining.mp4 13.2 MB
6. Prompt Templates Deep Dive/16. Semantic similarity example selector.mp4 13.1 MB
3. LLMs and Text Generation/1. How do language models generate text.mp4 12.5 MB
3. LLMs and Text Generation/4. Prompt engineering.mp4 11.9 MB
9. The LLM Landscape/2. The LLM landscape.mp4 11.9 MB
1. Introduction/1. Create powerful LLM driven applications.mp4 11.7 MB
6. Prompt Templates Deep Dive/13. Length-based example selector.mp4 11.4 MB
6. Prompt Templates Deep Dive/12. Introduction to example selectors.mp4 10.7 MB
3. LLMs and Text Generation/3. Training fine-tuning and in-context learning.mp4 10.6 MB
6. Prompt Templates Deep Dive/4. Serializing prompts.mp4 10.5 MB
9. The LLM Landscape/1. Applications of language models.mp4 10.1 MB
4. Components of LangChain/1. What is LangChain.mp4 9.6 MB
2. Introduction to Language Models/1. What are language models.mp4 9.1 MB
4. Components of LangChain/2. LangChain overview.mp4 8.8 MB
8. Prompt Management a.k.a. PromptOps/1. Prompt management.mp4 5.6 MB
5. Basics of Prompting/1. Prompt basics.mp4 4.2 MB
8. Prompt Management a.k.a. PromptOps/2. LangSmith.mp4 3.8 MB
Ex_Files_Prompt_Engineering_LangChain.zip 221.7 KB

Linkedin - Prompt Engineering with LangChain

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