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Learn effective prompt engineering techniques for GPT-3 and other LLMs. Explore anatomy, temperature, few-shot training, external information, and context windows to enhance AI-generated outputs.
Introduction to LangChain framework for building apps with large language models, comparing GPT-3 and open-source alternatives, and exploring key components for advanced NLP applications.
Learn to build a generative question-answering system using open-source AI and Python. Covers architecture, data preprocessing, embedding, indexing, and querying with BART for multi-sentence answers to open-ended questions.
Learn to create a chatbot and conversational agent using Falcon 40B, the top open-source LLM, with Hugging Face Transformers and LangChain. Explore code generation, refactoring, and agent capabilities.
Learn to interact with web APIs using Python, covering essentials like JSON, requests, and real-world examples with Google Geocoding and GitHub APIs.
Explore chatbot memory implementation in LangChain, including Conversation Chain, Summary Memory, and Buffer Window Memory. Learn to enhance AI conversations with context retention.
Learn to enhance Llama 2 using Retrieval Augmented Generation (RAG). Build a pipeline with Pinecone, Llama 2 13B, and integrate it using Hugging Face and LangChain for improved, up-to-date language model performance.
Learn to enhance LLM accuracy using retrieval augmentation in LangChain. Explore data preprocessing, embedding creation, vector database setup, and generative question-answering with citations for improved AI responses.
Build a multi-modal hybrid search engine for e-commerce using OpenAI's CLIP, BM25, and Python. Learn to process text and image queries, create embeddings, and implement efficient search functionality with Pinecone vector database.
Explore multilingual semantic search using Cohere's new model, comparing it with OpenAI's GPT 3.5. Learn implementation, data preparation, vector indexing, and query techniques for enhanced search capabilities.
Explore LangChain's chat features, including ChatOpenAI object, message types, and prompt templates. Learn to leverage these tools for enhanced AI interactions and natural language processing applications.
Learn to build a conversational agent using LangChain and GPT-3.5, leveraging vector search retrieval to provide context from Lex Fridman's podcast for intelligent responses.
Enhance GPT-4's capabilities with retrieval augmentation, using Pinecone vector database to provide up-to-date information and reduce hallucinations in AI-generated responses.
Learn to create custom tools for chatbots using LangChain, enhancing AI capabilities with web search, math, code execution, and image understanding. Explore practical examples and advanced agent techniques.
Explore an AI assistant that interacts with ArXiv papers using LangChain agents, OpenAI models, and Pinecone vector database, enabling enhanced research capabilities.
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