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  1. Automl
    1. Google Artificial Intelligence Platform
    2. Vertex ai tutorial
    3. Google vertex

Automl

I.C.T.: Information and Communication Technologies, also known as ICT, are the set of technologies developed to manage information and send it from one place to another. http://www.serviciostic.com/las-tic/definicion-de-tic.html6.

URL: is a Uniform Resource Identifier (URI) whose referenced resources can change, that is, the address can point to variable resources over time.https://es.wikipedia.org/wiki/Localizador_de_recursos_uniforme8.

WIKI: The name given to a web site, whose pages can be edited directly from the browser, where users create, modify or delete content that they generally share.https://es.wikipedia.org/wiki/Wiki7.

STORAGE: the action of saving documents or information in optical or electromagnetic formats in a computer, however, this action within companies implies a greater responsibility due to the value of what is stored.http://www.consultor-it.com/articulo/44001/que-es-storage10.

Google Artificial Intelligence Platform

Categories and types of Personal Information we collect. We collect Personal Information about you when you use the Products or Services, including individual identifiers, customer records, electronic network information, inferences and business information.

Categories of Sources of Personal Information Personal Information collected in the context of Products and Services is collected from original sources, customer sources, product sources, service sources, and third party sources.

Categories and Types of Personal Information We Collect. We collect Personal Information about you in the context of social networks, including individual identifiers, customer records, inferences, electronic network information, geolocation data, professional and employment information, and confidential information protected by law.

Third-Party Advertising. In addition to the third-party advertising companies we use to deliver advertising related to goods and services that may be of interest to you when you access and use social networks, a third-party social network provider may provide further advertising. Please review the privacy policies of the third-party social networks for their advertising and privacy policies.

Vertex ai tutorial

JSON data can be provided in different formats. IP Insights follows the common SageMaker formats standards. For more information on inference formats, see Common Data Formats for Inference.

Advanced users can access the entity learned from the IP model and embeddings by providing the additional content type parameter verbose=True in the Accept header. You can use entity_embedding and ip_embedding for model debugging, visualization and understanding. In addition, you can use these embeddings in other machine learning techniques, such as clustering classification.

Google vertex

But what about new customers? Traditional approaches can calculate these values with existing customers with extensive purchase histories, but they don't work very well for customers with little historical data. What if you could create a system to predict these values and increase the speed at which you deliver personalized marketing programs to customers?

Imagine your business has a contact form on its website. Every day you receive many messages from the form, many of which are practical in some way. Because they all come together, it's easy not to be able to deal with them all. Different employees control different types of messages.

You'll need a system to look at the comments and decide whether they represent complaints, praise for past service, attempts to get more information about your business, a request to schedule an appointment, or whether they're looking to establish a relationship.

You have a large library of gaming videos that you would like to use for analysis. However, there are hundreds of hours of video to review. Watching each video and manually marking segments to highlight each action is a tedious, time-consuming task. And you must repeat this work every season. Now imagine a computer model that can automatically identify and flag these actions every time they appear in a video.

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