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Neuton Use Cases for Neural Network and Machine Learning

Personal recommendations
Challenge:
Online service users expect more personalized recommendations be it music, movies, books, travel tours, or people. For companies that have thousands of products and millions of customers, it is impossible for human teams to make all recommendations manually.
Solution:
Recommendation engines based on neural network frameworks make recommendations that would benefit the customer most, thus increasing the possibility of a conversion. Some of the examples are YouTube “Recommended Videos” or Netflix “Other Movies You May Enjoy”. It is applicable to other industries such as travel, social networks, dating websites, mass media, etc.
Why Neuton:
Neuton generates models that make predictions much faster than those built with other AI solutions, thus making it possible to deliver personalized recommendations on the fly. In addition, it is so easy to use that any marketer can handle it.
Personalized Content
Challenge:
In social networks, it is difficult to see the information you really need. The flow of news from friends and companies is very large. In this vein, marketing should use personalized content for its audience.
Solution:
With the help of artificial intelligence, you can make your advertising campaigns as personalized as possible, attracting only the audience that is important for the promotion of a product or service. Since AI gives accurate forecasts, working with algorithms is very profitable.
Why Neuton:
Neuton is able to choose the right audience to target your new service or product, even if your social network group does not have many subscribers. Neuton is as effective working with large datasets as with small ones. Furthermore, its models work very fast enabling marketers to deliver personalized messages to their user feeds on the fly.