Databricks Machine Learning & AI Platform | Databricks
Databricks makes it simple to deploy, govern, query and monitor access to LLMs and integrate them into your workflows, and provides platform capabilities for retrieval augmented generation (RAG) or fine-tuning LLMs using your own data, resulting in better domain performance.
AI and machine learning on Databricks
AI and Machine Learning on Databricks, an integrated environment to simplify and standardize AI, ML, DL, and LLM development. Tutorials and user guides for common tasks and scenarios.
Get started: Build your first machine learning model on Databricks
Learn how to build a simple machine learning classification model on Databricks using the scikit-learn library.
Production Machine Learning - Databricks
One platform for data ingest, featurization, model building, tuning, and productionization simplifies handoffs. Automatically track experiments, code, results and artifacts and manage models in one central hub. Meet compliance needs with fine-grained access …
Machine Learning Model Development - Databricks
Machine Learning Model Deployment. This course is designed to introduce three primary machine learning deployment strategies and illustrate the implementation of each strategy on Databricks. Following an exploration of the fundamentals of model deployment, the course delves into batch inference, offering hands-on demonstrations and labs for ...
Databricks Runtime for Machine Learning | Databricks on AWS
Databricks Runtime for Machine Learning (Databricks Runtime ML) automates the creation of a cluster with pre-built machine learning and deep learning infrastructure including the most common ML and DL libraries.
Machine learning - Databricks
May 16, 2022 · These articles can help you with your machine learning, deep learning, and other data science workflows in Databricks.
Tutorials: Get started with AI and machine learning - Azure Databricks
Oct 9, 2024 · Learn how to use Azure Databricks throughout the machine learning lifecycle. This guide steps through key stages such as data loading and preparation; model training, tuning, and inference; and model deployment and management.
Graph and network analysis on Databricks | Databricks on AWS
October 11, 2024. This article gives an overview of Databricks capabilities for graph analysis and an introduction to basic graph concepts. Graphs are also commonly called networks, especially in the context of a specific area of study, such as social networks, or communication networks. A graph is a set of vertices that are connected by edges.
Azure Databricks AutoML data preparation and processing
Jul 3, 2024 · This article describes how Azure Databricks AutoML prepares data for machine learning training and describes configurable data settings. You can adjust these options during experiment setup in the AutoML UI. For configuring these settings using the AutoML API), refer to the AutoML Python API reference. Supported data feature types.
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