Allowing users to upload data, train models, and perform predictions without ML experience. Accelerates the creation of instant personalized user experiences at scale: Amazon Personalize does not require ML expertise, allowing developers to easily build instant personalized recommendations to provide optimal computing services to customers in industries such as retail, media and entertainment. Automatically capture printed, handwritten, and data: Amazon Textract uses optical character recognition to read and process any type of document using ML, accurately capture text,
Handwriting, forms, and other data without any bulk sms service manual effort . Execute and scale big data workloads with ease: Amazon EMR uses open source analytics frameworks such as Apache Spark, Apache Hive, and Presto to run large-scale distributed data processing jobs, interactive SQL queries, and ML applications. Join the AWS Proof of Concept (POC) program today and receive $300! What other advantages can artificial intelligence technology bring? AI technology has penetrated into manufacturing, logistics, e-commerce, retail sales, games, and even the financial industry. If you are still hesitant, you may wish to check whether your product or service has the following demand scenarios: Optimize user experience: Improve personalized recommendation on web pages, optimization of shopping/return process, intelligent customer service assistant, etc. Improve order conversion rate: Optimize the recommendation modules such as the home page, product detail page, and checkout page, optimize the push content and list, and increase product clicks on the category page and search result page.
Reduce management/development costs: Promotional discounts to maximize profits, new product development forecasts, distribution channel demand management, equipment predictive maintenance, shelf analysis. Improve user stickiness: Personalized level/gift pack/reward recommendation, prolong usage time, and improve user retention. Customer and process management: false data and account exclusion, user label classification, file asset identification and inventory. The above demand scenarios are only a small part of common AI technology applications. If you want to know more about the technical application possibilities of machine learning and deep learning, you can join AWS