Machine Learning for Anomaly Detection

Machine Learning for Anomaly Detection

  • Posted by Wilker Amorim
  • On December 8, 2019
  • AI, Communications, Machine Learning, Symphony Platform, Telecommunications, Time Series Forecast
Build and implement an AI solution to monitor, analyze and alert Communications companies of deviations from normal traffic behavior, detecting robocalling and fraud.
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 Programming With Data

Programming With Data

  • Posted by Daitan
  • On November 5, 2019
  • Data, Data Centers, Data Science, Machine Learning
In this post, I will share a very basic view of the technologies that are used to build ML solutions with the goal of helping those who have not had exposure to this domain understand where all the hype comes from. For my engineering colleagues, keep in mind that this article is meant to very simply present this technically complex field; and, does not tackle detailed technical challenges, the compelling issue of bias, and social concerns about ML/AI replacing jobs.
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 Storing and Retrieving Machine Learning Models at Scale With Distributed Object Storage

Storing and Retrieving Machine Learning Models at Scale With Distributed Object Storage

  • Posted by Daitan Innovation Team
  • On September 6, 2019
  • Machine Learning, Object Storage
The need to quickly create, store, and fetch machine learning models at scale is rapidly increasing. Examples of applications include recommender systems that are based on individual customers’ purchasing habits or detection of fraud attempts based on each customer’s past behavior, among many others.
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 Exponential Smoothing Methods for Time Series Forecasting

Exponential Smoothing Methods for Time Series Forecasting

  • Posted by Daitan Innovation Team
  • On August 7, 2019
  • Exponential Smoothing, Machine Learning, Time Series Forecast
In our last two articles, we covered basic concepts of time series data and decomposition analysis. Following that, it’s now time to apply that knowledge to a practical algorithm. In this piece, we provide an overview of Exponential Smoothing Methods.
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 Practical Facts About the Current State of Machine Learning and Artificial Intelligence

Practical Facts About the Current State of Machine Learning and Artificial Intelligence

  • Posted by Daitan
  • On August 11, 2018
  • AI, Data, Digital Transformation, Machine Learning
Over the past 2 years, Daitan has helped a number of our clients implement advanced technology solutions, as well as provided Data Science, Data Engineering, Customer Experience and DevOps resources to successfully implement it. In our experience, companies are taking measured steps to take advantage of Machine Learning and Artificial Intelligence technologies based on clear business objectives that intelligently further growth.
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