AI and ML
Documentation and resources for Google Cloud AI and ML products, covering platforms, pre-trained models, and tools for building smart applications.
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Explore AI and ML in Google Cloud
Read documentation and Cloud Architecture Center articles about AI and ML products, capabilities, and procedures.
Introduction to machine learning on Vertex AI
Support data engineering, data science, and ML engineering workflows on a unified platform, enabling you to train ML models and deploy AI solutions.
AI and ML architecture resources
Plan your approach with architecture center resources across a wide variety of AI & ML subjects. (Goes to Architecture Center.)
Best practices for implementing ML
Plan for implementing ML, with a focus on custom-trained models based on your data and code. (Goes to Architecture Center.)
Training, blog articles, and more
Go to training courses, blog articles, and other related resources.
Applied AI summit learning path
Study Vertex AI and Gemini in Google Cloud. (Goes to Google Cloud Skills Boost.)
Machine learning engineer learning path
Study designing, building, productionalizing, optimizing, operating, and maintaining ML systems. (Goes to Google Cloud Skills Boost.)
AI and ML products by use case
Expand sections or use the filter to find products and guides for typical use cases.
Pretrained models
Build AI applications with enterprise-grade scaling, security, and observability.
Cloud Vision API
Integrate vision detection features within applications, including image labeling, face and landmark detection, optical character recognition (OCR), and tagging of explicit content.
Video Intelligence API
Enable users to annotate videos stored locally or in Cloud Storage, or live-streamed, with contextual information at the level of the entire video, per segment, per shot, and per frame.
Cloud Natural Language API
Use natural language understanding technologies, including sentiment analysis, entity analysis, entity sentiment analysis, content classification, and syntax analysis.
Timeseries Insights API
Provide real-time forecasting and anomaly detection results.
Model Garden
Discover, test, customize, and deploy select OSS models and assets from an ML model library.
Customer service, conversation, and speech
Apply Google's state-of-the-art capabilities to handle your conversation, speech, and customer service needs.
Vertex AI Agents
Enable your end users to have conversations about the content using a virtual data store agent powered by large language models.
Text-to-Speech
Convert text to natural-sounding speech using ML.
Speech-to-Text
Integrate Google speech recognition technologies into developer applications.
Speech-to-Text on-prem
Integrate Google speech recognition technologies into your on-premises solution.
Speech On Device
Provide server-quality speech technology on embedded devices.
Conversational Insights
Detect and visualize patterns in contact center data.
Google Cloud Contact Center as a Service
Queue and route customer interactions across voice and digital channels to the appropriate resource pools, including allowing a seamless transition to human agents.
Dialogflow CX
Handle concurrent conversations with your end-users using a virtual agent that understands the nuances of human language.
Dialogflow ES
Design and integrate a conversational user interface into your mobile app, web application, device, bot, interactive voice response system, and so on.
Agent Assist
Empower human agents with continuous support during calls by identifying intent and providing real-time, step-by-step assistance.
Google Agentspace
A suite of cloud based AI agents, powered by Google-quality search and Gemini's advanced capabilities that transform knowledge work.
Conversational AI Platform
A collection of conversational AI tools, solutions and APIs, both designers and developers can use.
Document management
Apply Google's state-of-the-art capabilities to handle your document management needs.
Document AI
Transform unstructured data from documents into structured data, making it easier to understand, analyze, and consume.
Document AI processors
View a list of all processors by solution type.
OCR On-Prem
Integrate Google optical character recognition (OCR) technologies into your on-premises solution. (Deprecated)
Document AI Warehouse
Store, search, organize, govern and analyze documents and their structured metadata called properties. (Deprecated)
Industry-specific products
Apply Google's state-of-the-art capabilities to handle your industry-specific needs.
Anti Money Laundering AI
Detect suspicious, potential money laundering activity faster and more precisely with AI.
Optimization AI
Solve your operational optimization problems rapidly and at massive scale.
Talent Solution
Service that brings machine learning to the job search experience, returning high quality results to job seekers far beyond the limitations of typical keyword-based methods.
Telecom Subscriber Insights
Enable communication service providers to extract information to recommend actions to telecom customers.
Vertex AI Search for retail
Ingest user event and catalog data and serve predictions or search results on your site.
Media and entertainment solutions
Transform audience experiences with innovation and insights. (Goes to Google Cloud home.)
Video, images, vision, and augmented reality
Apply Google's state-of-the-art capabilities to handle your video, images, vision, and augmented reality needs.
Live Stream API
Convert live video and package it for streaming.
Transcoder API
Convert video files and package them for optimized delivery to web, mobile, and connected TVs.
Vertex AI Vision
Process and analyze your video streams and images at scale. Quickly build an application and deploy it to Google Cloud, using the built-in, low-code user interface.
Video Stitcher API
Dynamically insert ads into video-on-demand and live streams.
Immersive Stream for XR
Deliver rich, interactive 3D and augmented reality (AR) experiences to more devices by using cloud-based computing power.
Search and recommendations
Apply Google's state-of-the-art capabilities to handle your search and recommendations needs.
Vertex AI Search
Understand user intent and return the most relevant results and recommendations for the user with a search bar in your web pages or app providing Google-quality search app on your own data.
Vector Search
Perform vector similarity search so that you can conduct efficient, accurate searches on large amounts of data.
Enterprise Knowledge Graph
Organize siloed information into organizational knowledge, which involves consolidating, standardizing, and reconciling data in an efficient and useful way.
Translation
Apply Google's state-of-the-art capabilities to handle your conversation, speech, and customer service needs.
Cloud Translation API
Dynamically translate text programmatically through an API in your websites and applications, including document translation, custom translation, adaptive translation, transliteration, and romanization.
Translation Hub
Translate a large volume of documents into many different languages without building or maintaining your own web application or underlying infrastructure.
Vertex AI model training and development
Train ML models from your data using AutoML or your preferred ML framework.
Automatic training
Vertex AI with AutoML tabular
Vertex AI lets you perform machine learning with tabular data using simple processes and interfaces.
Vertex AI with AutoML image
Use machine learning analyzing the content of image data to classify image data or find objects in image data.
Vertex AI with AutoML video
Analyze video data to classify shots and segments, or to detect and track multiple objects in your video data.
Vertex AI with AutoML text
Train an ML model to classify text data, extract information, or understand the sentiment of the authors.
Custom training
Vertex AI training
Operationalize large scale model training.
Vertex AI Neural Architecture Search
Search for optimal neural architectures in terms of accuracy, latency, memory, a combination of these, or a custom metric.
Ray on Vertex AI
Perform distributed computing and parallel processing for your machine learning (ML) workflow.
Deep Learning Containers
Use a set of Docker containers with key data science frameworks, libraries, and tools pre-installed to provide you with performance-optimized, consistent environments that can help you prototype and implement workflows quickly.
Deep Learning VM Images
Use set of virtual machine images optimized for data science and machine learning tasks with key ML frameworks and tools pre-installed to accelerate your data processing tasks.
Vertex AI MLOps and production
Apply operations best practices to monitor and improve your deployed ML models.
Data and features
Vertex AI datasets
Use a managed dataset to provide the source data used to train AutoML and custom models on Vertex AI.
Vertex AI Feature Store
Streamline your ML feature management and online serving processes by managing your feature data in a BigQuery table or view and serving features online directly from the BigQuery data source.
Deployment
Vertex AI Inference
Get predictions from your models on Vertex AI.
Developer tools
Colab Enterprise
Use a collaborative, managed notebook environment with the security and compliance capabilities of Google Cloud.
TensorFlow Enterprise
TensorFlow Enterprise makes it easier to develop and deploy TensorFlow models on Google Cloud, by providing users with a set of products and services, which provide enterprise-grade support and cloud scale performance.
Vertex AI Workbench - Managed
Use a Google-managed environment with integrations and capabilities that help you set up and work in an end-to-end Jupyter notebook-based production environment. (Deprecated)
Vertex AI Workbench - User-managed
Use an integrated and secure JupyterLab environment preinstalled with the latest data science and machine learning frameworks for data scientists and machine learning developers to experiment, develop, and deploy models into production. (Deprecated)
Model iteration
Vertex AI Experiments
Track and analyze different model architectures, hyperparameters, and training environments, letting you track the steps, inputs, and outputs of an experiment run, plus evaluate how your model performed in aggregate, against test datasets, and during the training run.
Monitoring and evaluation
Vertex Explainable AI
Obtain feature-based and example-based explanations to provide better understanding of model decision making.
Vertex AI Model Monitoring
Provide model monitoring of feature skew and drift in the model's prediction input data for tabular AutoML and tabular custom-trained models.
Vertex AI model evaluation
Determine the performance of your models with model evaluation metrics, such as precision and recall.
Vertex AI TensorBoard
Track, visualize, and compare ML experiments and share them with your team.
Orchestration
Vertex AI Pipelines
Automate, monitor, and govern your machine learning (ML) systems in a serverless manner by using ML pipelines to orchestrate your ML workflows.
Vertex AI Model Registry
Manage the lifecycle of your ML models.
Accelerators
Accelerate machine learning workloads.
Cloud TPU
Accelerate machine learning workloads by accessing Tensor Processing Units (TPUs) from Compute Engine, Google Kubernetes Engine, and Vertex AI.
Related products, guides, and sites
Expand this section to see relevant products and documentation.
AI Hypercomputer
A supercomputer architecture that employs systems-level codesign to boost efficiency and productivity across AI training, tuning, and serving.
Generative AI on Google Cloud
Google Cloud offers a range of products and tools for the complete life cycle of building generative AI applications.
Overview of industry solutions
Find APIs and other solutions for financial services, healthcare, media, and retail.
Gemini for Google Cloud overview
Provides an always-on collaborator that offers generative AI-powered assistance to a wide range of Google Cloud users, including developers, data scientists, and operators.
AutoML Tables
Automatically build and deploy state-of-the-art machine learning models on structured data at massively increased speed and scale. (Deprecated)
AI Platform
Take your ML projects from ideation to production and deployment, quickly and cost-effectively. (Deprecated)