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Time Series Analysis: The Basis of Predicting in Machine Learning

By |2022-08-10T09:16:23+02:00March 4th, 2022|Blog, Business, Computational Social Science, Concepts, Philosophy|

Data is vast and inherently hard to understand. So naturally, certain technologies, algorithms, and practices have been developed to help enhance the ways in which we understand, and ultimately use, data. The current trend states that all data is inherently valuable, however, this very much depends on what is considered to be of value. Algorithms [...]

Conversations Between Human and Machines

By |2022-08-10T09:16:24+02:00February 4th, 2022|Blog, Business, Concepts, Philosophy, Predictions|

Imagine a conversation between you and your computer. The words you speak become a beacon of understanding for the programming, and actions are taken based on what you ask of the screen. Our way of speaking, though socially centered, is able to be translated into a logically centered form of language for machines. Many of [...]

Training Ai with ecosystem.Ai

By |2022-08-10T09:16:25+02:00December 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 [...]

Recommender systems with personality

By |2022-08-10T09:16:42+02:00August 7th, 2021|Blog, Computational Social Science, Concepts, Data Science, Predictions|

Recommender systems in technology have become an integral part of human digital society. Human existence is saturated with options for everything, from swimwear brands to cellphone models, to cruise package options! Thus the adoption and use of recommenders has been wholly invited into almost every business. Since its inception in the 1970’s, recommenders have grown [...]

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