Use the integrated machine learning in MindsDB to forecast Shopify store metrics.

Learn how to measure customer support sentiment analysis using GPT, Airbyte, and MindsDB. Set up sentiment analysis of Intercom chats, extract and analyze the data with GPT models, and visualize the results using Metabase.

Learn how to chat with your data warehouse using Airbyte and LlamaIndex. Discover the power of querying databases with natural language, bypassing the need for SQL expertise and memorization of complex database schemas.

Learn how to set up a maintainable and scalable pipeline for integrating diverse data sources into large language models using Airbyte, Dagster, and LangChain.

Learn how to build a connector development support bot for Slack that knows all your APIs, open feature requests and previous Slack conversations by heart

Build a quick full-stack AI application which arranges your Asana tasks for you in order of priority using MIlvus, Airbyte Cloud, and Next.js.

Unlock the full potential of Large Language Models (LLMs) like ChatGPT with optimized data pipelines. Learn how to integrate and manage data from various sources using Airbyte, ensure scalability with Dagster, and streamline access with LangChain.

Learn how to install and set up Qdrant, a powerful vector database for AI applications. This beginner's guide walks you through basic operations to manage and query embeddings.

Learn how to leverage Milvus and Airbyte to embed smart similarity search functionality into your applications

Learn how to build a full data stack using Airbyte Cloud, Terraform, and dbt to move data from S3 -> BigQuery -> Pinecone for interacting with fetched data through an LLM and form a full fledged RAG.

Learn how to build a full data stack using Airbyte Cloud, Terraform, and dbt to move data from Notion -> BigQuery -> Pinecone for interacting with fetched data through an LLM and form a full fledged RAG.

Learn how to build a full data stack using Airbyte Cloud, Terraform, and dbt to move data from S3 -> BigQuery -> Pinecone for interacting with fetched data through an LLM and form a full fledged RAG.