Resources to help you manage your data, responsibly
Google offers training, as well as access to free analytics tools and open-source privacy technologies that help businesses understand and manage their data more effectively and responsibly. We also highlight research, share insights, and identify key trends that can be used to inspire transformational ideas.
By type
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training
Grow with Google
Free training, tools, and resources to help you grow your skills, career, or business.
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training
Google News Initiative: Training Center
Training in digital skills and resources to journalists across the world.trains journalists in digital skills.
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training
Udacity Deep Learning
Training in digital skills and resources to journalists across the world.trains journalists in digital skills.
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training
Google Partners
For online advertising professionals, provides training from product experts and certification in Google advertising solutions.
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training
Skillshop
Master the Google tools you use at work with free online training
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training
Kaggle.com
The world's largest data science and machine learning community, and includes training courses, data sets and machine learning competitions.
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training
QuikLabs
A hands-on training platform to help you become a cloud expert with modules about machine learning, big data, security, and more.
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training
Launchpad Studio
A fully-tailored product development acceleration program that matches top machine learning startups and experts from Silicon Valley with the best of Google - its people, network, and advanced technologies - to help accelerate applied ML and AI innovation.
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training
Machine Learning Crash Course
Google's fast-paced, practical introduction to machine learning, Machine Learning Crash Course features a series of lessons with video lectures, real-world case studies, and hands-on practice exercises.
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training
Learn with Google AI
Offers a set of educational resources developed by machine learning experts at Google for people to learn concepts, develop skills, and apply artificial intelligence to real world problems.
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training
Grasshopper
A free mobile app that teaches you how to code using quick games.
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training
Product Controls
Data is critical to your business, so it’s essential that it’s managed in the right way. With Google you can be confident that, no matter which of our products and services you use, you’ll have control over what information you share.
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technology
Built-In Security
Built-in, Automatic Protection
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technology
Security & Privacy for All
We have a long history of developing Internet security technology that benefits our own users and the online world as a whole. So when we create technology to keep our services safer, we find opportunities to share it for everyone’s benefit.
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training
Compliance
We are committed to complying with applicable data protection laws
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research
Data Safety
Protecting data starts with the world's most advanced security
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training
Responsible Innovation
We know the value that data has to your business, which is why we aim to help you gain insights from it in the most effective and responsible ways.
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research
Think With Google
Uncover the latest marketing research and digital trends with data reports, guides, infographics, and articles.
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research
Research at Google
Researchers across Google are innovating across many domains. We challenge conventions and reimagine technology so that everyone can benefit.
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tools
Playground.tensorflow.org
Play with a neural network right in your browser.
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tools
Google Open Source
Free, open-source software has been part of Google's technical and organizational foundation since the beginning. Google Open Source summarizes all of our initiatives, with information on how we use, release and support open source.
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tools
TensorFlow
"This open-source machine learning tool can be used to extract value from and improve the quality of your data, without sharing anything in return. It's been used to improve many Google services, from Google Translate to speech recognition."
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tools
Google Analytics
Implement this tool to help understand your business's web or app traffic data, including aggregated demographic and device data, and benchmark reports based on your business' peers.
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tools
Google Trends
A publicly available tool that can help businesses analyze Google’s aggregated Search history and identify trends. It's used to predict everything from flu outbreaks to election results.
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tools
Android UMP SDK
To support publishers in meeting their duties under EU ePrivacy Directive and the General Data Protection Regulation (GDPR), Google has extended Funding Choices to support apps with the addition of the UMP SDK. This solution is replacing the previous Consent SDK solution.
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tools
iOS UMP SDK
To support publishers in meeting their duties under EU ePrivacy Directive and the General Data Protection Regulation (GDPR), Google has extended Funding Choices to support apps with the addition of the UMP SDK. This solution is replacing the previous Consent SDK solution.
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tools
Facets
An open source visualization tool for machine learning training data.
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tools
Teachable Machine
A simple experiment that lets you teach a machine using your camera – all in your browser, no coding required.
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technology
TensorFlow Privacy
We scale differential privacy protection with TensorFlow Privacy – an open source library that makes it easy for developers to train machine-learning models with privacy. It also helps researchers to advance the state-of-the art in machine learning with strong privacy guarantees.
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technology
Differential Privacy Library
Using differential privacy, we can train machine learning models and compute statistics with heightened privacy standards, doing more for users with less data. This technology allows us to prevent a model from memorizing information that could reveal specific details about a user. We published early research on this topic in 2014, and since then we’ve used it in Chrome, in Gmail with Smart Compose, and in Google Maps to show you how busy a restaurant is or to recommend a popular dish.
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technology
Private Join & Compute
Private Join & Compute is a secure, multi-party computation technology that keeps individual information safe while drawing insights from aggregated statistics. By making this technology available through our open-source model, we hope to expand the use cases for secure computing and help organizations work with confidential datasets while preserving the highest level of user privacy. We also hope it will advance valuable research in a wide array of fields that require organizations to work together while upholding user privacy. For example, when industries create new programs to close gender and racial pay gaps, Private Join & Compute could help us understand how this impacts compensation across companies by demographic, without revealing anything about individuals represented in the data.
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technology
Federated Learning
Federated learning is a new approach to machine learning that allows our products to work better, without data leaving your device. This technology allows developers to make products smarter by enabling many devices to collaboratively train AI models. By processing more of the data right where it is created, we can create smarter features that benefit everyone, without collecting sensitive data. Federated learning is already powering smarter experiences across millions of phones, in products including Gboard and Pixel.
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technology
Data Transfer Project
The Data Transfer Project was launched in 2018 to create an open-source, service-to-service data portability platform so that all individuals across the web could easily move their data between online service providers whenever they want. The contributors to the Data Transfer Project believe portability and interoperability are central to innovation. Making it easier for individuals to choose among services facilitates competition, empowers individuals to try new services and enables them to choose the offering that best suits their needs.
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datasets_and_apis
Maps API
Your business can embed a Google Map into its app or website with aerial and satellite imagery, directions, and local business information.
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datasets_and_apis
Earth Engine
Earth Engine is a multi-petabyte catalog of satellite imagery and geospatial data sets, combined with planetary-scale analysis capabilities. Earth Engine is available for scientists, researchers, and developers to detect changes, map trends, and quantify differences on the Earth's surface.
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datasets_and_apis
BigQuery Data Sets
Google regularly publishes datasets for research use on our Research Blog.
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datasets_and_apis
Video Data Sets
For the benefit of machine learning research, we have opened up a large-scale labeled video data set that consists of millions of YouTube video IDs and associated labels.
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datasets_and_apis
Safe Browsing URL Database
Our Safe Browsing technology provides an API service that lets applications check URLs against Google's constantly updated lists of unsafe web resources. Examples of unsafe web resources are social engineering sites (phishing and deceptive sites) and sites that host malware or unwanted software, all of which pose threats to security and privacy.
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datasets_and_apis
AVA
A publicly available video dataset that recognizes and labels multiple human actions, essential to personal video search and discovery, sports analysis, and gesture interfaces.
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datasets_and_apis
Google Trends News Lab Datastore
Datasets from Google Trends curated by the News Lab at Google, and includes recent news articles and current affairs.
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datasets_and_apis
Open Images Dataset
A dataset of ~9 million images that have been annotated with image-level labels and object bounding boxes. The images are very diverse and often contain complex scenes with several objects (8.4 per image on average) and the dataset is annotated with image-level labels spanning thousands of classes.
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datasets_and_apis
Quick, Draw! Dataset
A unique dataset of doodles. The Quick Draw Dataset is a collection of 50 million drawings across 345 categories, contributed by players of the game Quick, Draw! They can be used to help developers train new neural networks, help researchers see patterns in how people around the world draw, and help artists create things we haven’t begun to think of.
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datasets_and_apis
Google Dataset Search
Find publicly available datasets hosted on the web.
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case_studies
Using data to digitizing Thomas Cook’s legacy brochure business via “Hotel Everywhere"
Thomas Cook wanted to digitally transform their $40m+ media and partnerships business to monetise their owned and operated digital inventory and audience. The end result is Hotel Everywhere where users can share data on the type of hotel they are looking for, and Thomas Cook is able to provide relevant ads both on and offline by securely sharing this data with advertising partners.
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case_studies
Global Fishing Watch: Using satellite data to prevent overfishing
"In partnership with Oceana and SkyTruth we’re combining cloud computing and satellite data to create the first global view of commercial fishing activities. Global Fishing Watch uses machine learning to analyze more than 22 million data points per day to create an animated heat map that anyone can view. This platform, which wasn’t even technically feasible a few years ago, is now poised to change the way agencies, governments, and citizens manage our endangered ocean resources."
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case_studies
Smart Wildfire Sensor - fighting fires with TensorFlow
"Existing wildfire prevention tools can assess an area’s risk of wildfire by measuring things like wind speed, wind direction, humidity and temperature. But biomass, which consists of fire-fueling materials like dead trees and debris, is hard to measure. Two teenagers created categories for the different types of biomass fuel and then trained a machine learning model to recognize relevant data about the fuels. This technology could help warn emergency responders about high-risk levels of biomass, allowing them to prevent fires before they even start."
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case_studies
Using ML to help drive efficiencies in cucumber farming in Japan
Makoto Koike wanted to automate the time-consuming and expensive process of sorting cucumbers in order to have more time to focus on growing the vegetables. Using deep learning for image recognition, the computer was able to learn from a training data set what the important "features" of the cucumbers are, and therefore sort them according to Makoto’s criteria. The low barriers to entry for this type of ML via TensorFlow have enabled “non-ML” engineers like Makoto to make the most out of the technology using their own datasets and applications.
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technology
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