https://insidebigdata.com/tag/alegion/ Your Source for AI, Data Science, Deep Learning & Machine Learning Strategies Wed, 19 Oct 2022 15:37:31 +0000 en-US hourly 1 https://wordpress.org/?v=6.3.2 136462205 https://insidebigdata.com/2019/04/11/ai-ready-three-keys-success/ https://insidebigdata.com/2019/04/11/ai-ready-three-keys-success/#respond Thu, 11 Apr 2019 13:30:13 +0000 https://insidebigdata.com/?p=22432 Data scientists know what they are doing, and most organizations have no cause to worry about the soundness of their machine learning (ML) algorithms. Where AI readiness typically lags is in other parts of the process. In most organizations today, the process of building, deploying and maintaining AI systems bears no resemblance to traditional IT. Alegion explores three key strategies your business can employ to be AI-ready. ]]> https://insidebigdata.com/2019/04/11/ai-ready-three-keys-success/feed/ 0 22432 https://insidebigdata.com/2019/03/25/checkling-machine-learning-training-data/ https://insidebigdata.com/2019/03/25/checkling-machine-learning-training-data/#respond Mon, 25 Mar 2019 13:30:53 +0000 https://insidebigdata.com/?p=22312 Machine learning is often key to success for today's institutions that rely heavily on data for success. But often, data science teams can have a difficult time convincing their organizations of the breadth and size of a training data challenge. A new report from Alegion walks through a checklist to review before helping your enterprise take the next step in machine learning.]]> https://insidebigdata.com/2019/03/25/checkling-machine-learning-training-data/feed/ 0 22312 https://insidebigdata.com/white-paper/blueprint-machine-learning-training/ https://insidebigdata.com/white-paper/blueprint-machine-learning-training/#respond Fri, 15 Mar 2019 17:48:13 +0000 https://insidebigdata.com/?post_type=wpdmpro&p=22273 Download the new guide from Alegion that acts as a pre-flight checklist for data science teams that are contemplating preparing their own maching learning training data. ]]> 0 22273 https://insidebigdata.com/2019/03/12/ai-systems-machine-learning-bias/ https://insidebigdata.com/2019/03/12/ai-systems-machine-learning-bias/#respond Tue, 12 Mar 2019 13:30:11 +0000 https://insidebigdata.com/?p=22242 AI systems are becoming more and more of the norm as machine and deep learning gain grown — especially within the data center and colocation markets. That said, Artificial Intelligence systems are only as good as their underlying mathematics and the data they are trained on. Download a new report from Alegion to further understand the bias behind machine learning and how to avoid four potential pitfalls.]]> https://insidebigdata.com/2019/03/12/ai-systems-machine-learning-bias/feed/ 0 22242 https://insidebigdata.com/white-paper/four-types-machine-learning-bias/ https://insidebigdata.com/white-paper/four-types-machine-learning-bias/#respond Thu, 28 Feb 2019 16:49:57 +0000 https://insidebigdata.com/?post_type=wpdmpro&p=22211 0 22211 https://insidebigdata.com/2018/08/23/report-explores-machine-learning-ai-bias/ https://insidebigdata.com/2018/08/23/report-explores-machine-learning-ai-bias/#respond Thu, 23 Aug 2018 13:30:39 +0000 https://insidebigdata.com/?p=20960 https://insidebigdata.com/2018/08/23/report-explores-machine-learning-ai-bias/feed/ 0 20960 https://insidebigdata.com/2018/08/20/machine-learning-bias-ai-systems/ https://insidebigdata.com/2018/08/20/machine-learning-bias-ai-systems/#respond Mon, 20 Aug 2018 13:30:19 +0000 https://insidebigdata.com/?p=20957 https://insidebigdata.com/2018/08/20/machine-learning-bias-ai-systems/feed/ 0 20957 https://insidebigdata.com/white-paper/four-sources-machine-learning-bias/ https://insidebigdata.com/white-paper/four-sources-machine-learning-bias/#respond Fri, 17 Aug 2018 14:00:21 +0000 https://insidebigdata.com/?post_type=wpdmpro&p=20951 As a company that specializes in training AI systems, we know only too well that AI systems do precisely what they are taught to do. Models are only as good as their mathematical construction and the data they are trained on. Algorithms that are biased will end up doing things that reflect that bias.]]> 0 20951