Machine Learning

Machine Learning

Machine learning (ML) represents today’s most widely valued mechanism for reaching intelligence. It is a subfield of artificial intelligence. Instead of relying on explicit programming, it is a system through which computers use a massive set of data and apply algorithms to “train” on — to teach themselves — and make predictions.

Machine Learning for Healthcare

Doctors and medical practitioners will soon be able to predict with accuracy on how long patients with fatal diseases will live. Medical systems will learn from data and help patients save money by skipping unnecessary tests.

Machine Learning for Finance

The application of ML in the Finance domain helps banks offer personalized services to customers at lower cost, better compliance and generate greater revenue.

Machine Learning for Retail

Retailers need a solution that can analyze data in real-time and provide valuable insights that can translate into tangible outcomes like repeat purchasing. ML algorithms process this data intelligently and automate the analysis to make this supercilious goal possible.

Machine Learning for Travel

The travel industry leverages ML to analyze real-time data, trends and provide predictive modeling to provide insights into tourist behaviors, hotel reservations, and hotspot locations.

Machine Learning for Social Media

ML offers the most efficient means of engaging billions of social media users. From personalizing news feeds to rendering targeted ads, ML is the heart of all social media platforms for their own and user benefits. Social media and chat applications have advanced to a great extent that users do not pick up the phone or use email to communicate.

Machine Learning for Industries

In the automotive sector, ML is being used to improve industrial processes. As an example, factories carry out predictive analysis of component durability and in the early identification of anomalies and defects.

In installations and energy management, ML in this area is developing smart networks or smart grids.

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Google is a Leader in the 2022 Gartner® Magic Quadrant™ for Cloud AI Developer Services

Gartner named Google a Leader in the 2022 Gartner® Magic Quadrant™ for Cloud AI Developer Services report. This evaluation spans Google’s language, vision, and structured data products including AutoML, all of which we deliver through Google Cloud. Access your complimentary copy of the report to gain a comprehensive view of where the market is headed.

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Machine learning on Google Cloud Platform

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Train models without code

Take advantage of AutoML to build models in less time. Use Vertex AI with state-of-the-art, pre-trained APIs for computer vision, language, structured data, and conversation.

Build advanced ML models with custom tooling

Vertex AI’s custom model tooling supports advanced ML coding, with nearly 80% fewer lines of code required to train a model with custom libraries than competitive platforms.

Make faster decisions using data

Improve operational efficiency by extracting structured data from unstructured documents and making that available to your business apps and users.

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