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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.
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 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.
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.
Master OpenAI's Agents SDK v0.1 through hands-on tutorials covering voice assistants, multi-agent systems, handoffs, chat history, observability, and tools implementation.
Discover comprehensive LangChain v0.3 techniques for AI engineers, covering agents, memory, streaming, and real-world project implementation in 2025.
Explore practical frameworks and methods for building real-world AI systems, from chatbot guardrails to RAG optimization and agent development.
Master production-ready AI development using semantic router library with OpenAI, Cohere, Llama.cpp, and HuggingFace for steerable chatbots and agentic AI systems.
Discover computer vision techniques for search applications, from color histograms to CLIP models, with hands-on PyTorch implementations and zero-shot classification methods.
Discover how to host, build, and manage datasets on Hugging Face platform, including working with images and custom dataset builder scripts for machine learning projects.
Master vector similarity search techniques and Faiss implementation through hands-on practice with traditional methods, advanced indexing, and performance optimization strategies.
Master NLP techniques for semantic search and vector databases through dense vectors, sentence transformers, fine-tuning methods, and question-answering systems.
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