01 From AI to Agents| Fundamentals of AI | ML | DL | LLM & GenAI | How LLMs work | What are Agents
Summary
The video explains the fundamental concepts of AI, ML, DL, LLMs, and GenAI, illustrating their hierarchical relationship as subsets of each other. It also defines what models are (mathematical formulas trained on data) and how agents combine LLMs with tools and optional memory to perform autonomous tasks.
Summary generated by brickster.ai from the video transcript.
More from Ease With Data
Tutorials02 Machine Learning (ML) for Data Engineers | Basics of Machine Learning |Classification Regression
The video explains core machine learning concepts, including supervised, unsupervised, and reinforcement learning, along with the workflow for building and evaluating models. It details classification and regression models, their applications, and essential data preparation techniques like feature engineering and handling the curse of dimensionality.
NewsGenAI - For Data Engineers Agenda & Introduction | LLM & Agentic AI | LangChain & LangGraph | Claude
This video introduces a new course, "GenAI for Data Engineers," designed to teach data engineers how to leverage generative AI, LLMs, and agentic AI. The course covers basics of LLMs, building agents with LangChain and LangGraph, using Cloud Code, and applying agentic AI within Databricks and data engineering workflows.
Tutorials54 Zerobus Ingest Lakeflow Standard Connector | Ingest Streaming data directly into Delta Table
The video demonstrates how to use Databricks Zero Bus Ingest, a push-based API, to directly stream various data types like IoT, event, and telemetry data into Unity Catalog Delta tables. It highlights Zero Bus Ingest's ability to simplify streaming ingestion by eliminating the need for intermediate message buses and managing their infrastructure.
Tutorials53 Lakeflow Connect SQL Server Managed Connector | Ingest Data using Databricks native connectors
The video demonstrates how to ingest data from SQL Server into Databricks using Lakeflow Connect's managed connector, covering the setup of a SQL Server database, user permissions, and enabling change tracking/change data capture (CT/CDC). It then walks through configuring the Databricks connection, creating gateway and ingestion pipelines, and showcasing how SCD Type 2 changes are automatically managed.
Tutorials52 Lakeflow Spark Declarative Pipelines | New Pipeline Code Editor | AUTO CDC |External Target Sinks
Databricks' LakeFlow Spark Declarative Pipelines (SDP), formerly Delta Live Tables (DLT), offers a unified solution for data ingestion, transformation, and orchestration, now open-sourced with Apache Spark 4.1. The video demonstrates using the new pipeline code editor to build SDPs in Python and SQL, showcasing features like auto CDC (formerly apply changes) and external target sinks.
Tutorials34 Write PySpark Unit Test Cases using PyTest module | Setup PyTest with PySpark
The video demonstrates how to write PySpark unit test cases using the Pytest module. It covers setting up Pytest, creating fixtures for Spark sessions, and writing test functions to validate PySpark transformations and filters.