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Feb 14 32 “By integrating new automation features IBM is making machine learning more accessible for enterprise users that may not have the ninja data scientists on staff to cut down on time intensive but necessary tasks in the machine learning workflow like model selection and hyperparameter tuning
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live chatTowards Ultra High Performance and Energy Efficiency of Deep Learning Systems An Algorithm Hardware Co Optimization Framework Yanzhi Wang1 Caiwen Ding1 Zhe Li1 Geng Yuan1 Siyu Liao2 Xiaolong Ma1 Bo Yuan2 Xuehai Qian3 Jian Tang1 Qinru Qiu1 Xue Lin4 1Department of Electrical Engineering and Computer Science Syracuse University Syracuse NY
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live chatJan 09 32 Putting the ‘smart’ in ‘smart factory’ OKUMA’s new AI infused CNC control January 9 True to the company’s reputation as a single source provider of CNC solutions Okuma launched its next generation CNC control OSP P300A alongside their latest machine tools presented at the 28th Japan International Machine Tool Fair JIMTOF
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live chatApr 16 32 Covestro was skeptical about the value of machine learning models says Jane Arnold EVP and head of global process control technology but a study the company did on a large motor failure found that “through ML we could have detected anomalies starting eight months prior to failure”
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live chatSep 05 32 Machine learning ML pipelines consist of several steps to train a model but the term ‘pipeline’ is misleading as it implies a one way flow of data Instead machine learning pipelines are cyclical and iterative as every step is repeated to continuously improve the accuracy of the model and
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live chatMay 28 32 Model deployment Machine learning education tends to go quite in depth into the ML algorithms themselves teaching your how they work on a technical level Once your model is fully trained it’s common practice to then test it on a held out unseen test dataset to benchmark the model performance Once we’ve verified that our model works
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