Linkedin - Prompt Engineering with LangChain
- CategoryOther
- TypeTutorials
- LanguageEnglish
- Total size1.3 GB
- Uploaded ByxHOBBiTx
- Downloads124
- Last checkedMay. 16th '24
- Date uploadedMay. 15th '24
- Seeders 17
- Leechers11
Quote:
This course provides a comprehensive yet concise introduction to LangChain, a powerful framework for large language model (LLM) applications. Starting with the basics of LLMs, instructor Harpreet Sahota explores the key features and capabilities of LangChain, showing you how to integrate it with various systems and gain hands-on experience in building practical applications. Whether you're a seasoned developer or a beginner, this course will equip you with a solid foundation in LangChain, setting the stage for more advanced topics and applications.
Files:
Linkedin - Prompt Engineering with LangChain 1. Introduction- 1. Create powerful LLM driven applications.mp4 (11.7 MB)
- 1. What are language models.mp4 (9.1 MB)
- 1. How do language models generate text.mp4 (12.5 MB)
- 2. Base LLMs vs. instruction-tuned LLMs.mp4 (35.0 MB)
- 3. Training fine-tuning and in-context learning.mp4 (10.6 MB)
- 4. Prompt engineering.mp4 (11.9 MB)
- 1. What is LangChain.mp4 (9.6 MB)
- 2. LangChain overview.mp4 (8.8 MB)
- 3. Model I O- Interface with language models.mp4 (85.2 MB)
- 4. Retrieval- Interface with application-specific data.mp4 (58.4 MB)
- 5. Chains- Construct sequences of calls.mp4 (74.8 MB)
- 6. Agents- Let chains choose tools based on high-level directives.mp4 (55.4 MB)
- 7. Memory- Persist application state between runs of a chain.mp4 (40.3 MB)
- 1. Prompt basics.mp4 (4.2 MB)
- 2. Principles and tactics for prompting.mp4 (30.7 MB)
- 1. Introduction to prompt templates.mp4 (26.6 MB)
- 10. Few-shot prompt templates.mp4 (33.9 MB)
- 11. Few-shot prompt templates for chat.mp4 (22.2 MB)
- 12. Introduction to example selectors.mp4 (10.7 MB)
- 13. Length-based example selector.mp4 (11.4 MB)
- 14. Max marginal relevance example selector.mp4 (17.4 MB)
- 15. N-gram overlap example selector.mp4 (30.1 MB)
- 16. Semantic similarity example selector.mp4 (13.1 MB)
- 17. Partial prompt templates.mp4 (15.7 MB)
- 2. Multi-input prompt templates.mp4 (20.4 MB)
- 3. Chat prompt template.mp4 (21.6 MB)
- 4. Serializing prompts.mp4 (10.5 MB)
- 5. Zero-shot prompts.mp4 (21.1 MB)
- 6. Custom prompt templates.mp4 (31.2 MB)
- 7. Prompt pipelining.mp4 (25.8 MB)
- 8. Chat prompt pipelining.mp4 (13.2 MB)
- 9. Prompt composition.mp4 (18.0 MB)
- 1. Chain of thought.mp4 (38.9 MB)
- 2. Self-consistency.mp4 (29.6 MB)
- 3. Self-ask.mp4 (51.0 MB)
- 4. ReAct.mp4 (39.7 MB)
- 5. RAG.mp4 (80.7 MB)
- 6. FLARE.mp4 (50.5 MB)
- 7. Plan and execute.mp4 (56.8 MB)
- 1. Prompt management.mp4 (5.6 MB)
- 2. LangSmith.mp4 (3.8 MB)
- 3. LangSmith walkthrough.mp4 (24.4 MB)
- 4. Prompt versioning in LangSmith.mp4 (40.7 MB)
- 5. LangSmith deep dive.mp4 (48.5 MB)
- 6. Managing prompt length for agents.mp4 (33.0 MB)
- 1. Applications of language models.mp4 (10.1 MB)
- 2. The LLM landscape.mp4 (11.9 MB)
- Ex_Files_Prompt_Engineering_LangChain.zip (221.7 KB)
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