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Tag: Databricks

  • Top 10 LLMs on Hugging Face for Chatbot & RAG Use (Early May 2025)

    Top 10 LLMs on Hugging Face for Chatbot & RAG This list is based on a combination of factors including general popularity, instruction-following capabilities, context window size, and community interest relevant to chatbot and Retrieval-Augmented Generation (RAG) applications. 1. mistralai/Mixtral-8x7B-Instruct-v0.1 Use Cases: Excellent for instruction following, complex reasoning in chatbots, and can handle long contexts Read more

  • Top 10 LLMs on Hugging Face & Use Cases: Part 2

    Another Top 10 LLMs on Hugging Face & Use Cases Another Top 10 Popular LLMs on Hugging Face & Their Use Cases Here’s another selection of popular and interesting Large Language Models available on Hugging Face, showcasing the diversity of the open-source LLM landscape as of early May 2025. 1. google/gemma-7b-it Use Cases: Instruction tuning, Read more

  • Automating PDF to JSON Extraction with AI/ML

    Automating PDF to JSON Extraction with AI/ML 1. Understanding the Problem and Defining Key Values for AI/ML When leveraging AI/ML for PDF to JSON extraction, the initial problem definition remains crucial, but with a focus on how AI/ML can address challenges posed by unstructured or highly variable documents. Identify the Key Values: As before, define Read more

  • Processing Data Lakehouse Data for Machine Learning

    Processing Data Lakehouse Data for Machine Learning Processing Data Lakehouse Data for Machine Learning Leveraging the vast amounts of data stored in a data lakehouse for Machine Learning (ML) requires a structured approach to ensure data quality, relevance, and efficient processing. Here are the key steps involved: 1. Data Discovery and Selection Details: The initial Read more

  • Processing Data Lakehouse Data for Agentic AI

    Processing Data Lakehouse Data for Agentic AI Processing Data Lakehouse Data for Agentic AI Agentic AI, characterized by its autonomy, goal-directed behavior, and ability to interact with its environment, relies heavily on data for learning, reasoning, and decision-making. Processing data from a data lakehouse for such AI agents requires careful consideration of data quality, relevance, Read more

  • Building an Azure Data Lakehouse from Ground Zero

    Building an Azure Data Lakehouse from Ground Zero Building an Azure Data Lakehouse from Ground Zero: Detailed Steps Building a data lakehouse on Azure involves leveraging Azure Data Lake Storage Gen2 (ADLS Gen2) as the storage foundation, along with services like Azure Synapse Analytics, Azure Databricks, and Azure Data Factory for data processing and querying. Read more

  • Integrating with Azure Data Lakehouse: Real-Time and Batch

    Integrating with Azure Data Lakehouse: Real-Time and Batch Integrating with Azure Data Lakehouse: Real-Time and Batch Azure provides a comprehensive set of services to build a data lakehouse, primarily leveraging Azure Data Lake Storage Gen2 (ADLS Gen2) as the foundation, along with services for real-time and batch data integration and processing. Real-Time (Streaming) Integration Real-time Read more

  • Comparing BI Offerings: AWS, Azure, and GCP

    Comparing BI Offerings: AWS, Azure, and GCP Comparing Business Intelligence (BI) Offerings: AWS, Azure, and GCP Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) are the leading cloud providers, each offering a comprehensive suite of services for Business Intelligence (BI) and data analytics. While there’s feature overlap, they also have distinct strengths. Read more

  • Real-Time Ingestion of Salesforce Data into Azure Data Lake

    Real-Time Ingestion of Salesforce Data into Azure Data Lake Real-Time Ingestion of Salesforce Data into Azure Data Lake Ingesting data from Salesforce into Azure in real-time for a data lake typically involves leveraging event-driven architectures and Azure’s data streaming and integration services. Here are the primary methods: 1. Salesforce Platform Events or Change Data Capture Read more

  • Exploring the Synergy of Kafka and Databricks for Agentic AI

    Combining Apache Kafka and Databricks offers a powerful and comprehensive platform for building, deploying, and managing sophisticated agentic AI systems. Kafka excels at real-time data ingestion and stream processing, while Databricks provides a unified environment for big data processing, machine learning, and AI model development. Kafka’s Role in Agentic AI: Real-time Data Foundation Kafka provides Read more