Langchain For Developers Using OpenAI LLMs in Python

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Files Included :

1 - What is Langchain.mp4 (14.52 MB)
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2 - Understanding LLMs.mp4 (51.91 MB)
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3 - Installing Langchain & Hello World Example.mp4 (32.19 MB)
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4 - Different Types of Supported Models.mp4 (17.3 MB)
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5 - Working with LLM Models.mp4 (36.37 MB)
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6 - Chat Models In Langchain.mp4 (23.69 MB)
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7 - What Are Embeddings.mp4 (19.48 MB)
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8 - Using OpenAI Text Embeddings to Analyze Sentiment.mp4 (27.51 MB)
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10 - Prompting Best Practices Formatting Few Shot Prompting & CoT.mp4 (115.68 MB)
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11 - Using Langchains Builtin Prompt Templates.mp4 (30.13 MB)
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12 - Output Parsers in Langchain.mp4 (29.12 MB)
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14 - Managing Chatbot Memory in Langchain.mp4 (29.52 MB)
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15 - What is Chaining.mp4 (7.29 MB)
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16 - How To Build Chains in Langchain.mp4 (36.13 MB)
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17 - Langchain Document Loaders & Vectorstores.mp4 (41.29 MB)
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18 - What are Langchain Agents.mp4 (16.09 MB)
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19 - Working With Langchain Agents.mp4 (31.65 MB)
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20 - Building An Arxiv Summarizer Agent.mp4 (18 MB)
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22 - Document Loaders For Different Data Types & Sources.mp4 (63.57 MB)
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23 - Document Splitting Exploring Different Methods.mp4 (74.82 MB)
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24 - Recap on Vector Stores.mp4 (41.82 MB)
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25 - Advanced Retrieval Methods.mp4 (50.33 MB)
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26 - Querying Your Data with Chat Models.mp4 (58.92 MB)
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27 - Scaling Up Our Arxiv Research Bot.mp4 (73.04 MB)
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28 - Utilizing YouTube as a Data Source for Chatbot Models.mp4 (50.67 MB)
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29 - Hooking Up Our Chatbot to Wikipedia.mp4 (29.87 MB)
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