Exploring Dynamic Experimentation

By |2022-06-29T14:18:28+00:00June 21st, 2022||

7am San Francisco. 8am Denver. 9am Chicago. 10am New York. 3pm London. 4pm Paris. 4pm South Africa. 5pm Eastern Europe. meet.google.com/oox-kztk-vum Generate your own intelligent data, make money faster and reduce time to market, while your predictions are in production. Eliminate bias by allowing your models to learn through Dynamic Experimentation, and lower the cost of production while you [...]

Introduction to Dynamic Experimentation

By |2022-06-21T14:59:31+00:00June 21st, 2022||

7am San Francisco. 10am New York. 3pm London. 4pm South Africa. 4pm Europe meet.google.com/oox-kztk-vum Generate your own intelligent data, make money faster and reduce time to market, while your predictions are in production. Eliminate bias by allowing your models to learn through Dynamic Experimentation, and lower the cost of production while you make money.   [...]

Time in The World of ecosystem.Ai

By |2022-08-10T09:16:23+00:00March 18th, 2022|Blog, Concepts, Data Science, Product, Technology, Video|

Watch the full series: https://www.youtube.com/playlist?list=PLGKmyxwO1unIpimQEJUrQxPeTImyifKc3 Time has a very important place in human society, this is how ecosystem.Ai uses time based variables to ensure human behavioral attributes are always considered. https://youtu.be/02YqrjJuz-Q ecosystem.Ai uses time in a new way. Moving beyond statistical values alone, using various behavioral elements, understanding time in the context of the [...]

Training Ai with ecosystem.Ai

By |2022-08-10T09:16:25+00:00December 10th, 2021|Blog, Computational Social Science, Concepts, Demo's, Video|

Watch the full series: https://www.youtube.com/playlist?list=PLGKmyxwO1unL3acJKuekMY6-xSEbeX4Ll A recommender is the most engaged with system online. But not all recommenders work the way they should. This discussion was the start of a journey to help you simplify the complexities of the machine learning process. https://youtu.be/OtOPhpmMRFY   What ecosystem.Ai has prided themselves on is identifying, and paying [...]

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