Today, the capability and reach of artificial intelligence (AI) is continually expanding as the technology grows in complexity. As a result, engineers are faced with new challenges as they are tasked with integrating AI into systems. Part of the complexity stems from the recognition that AI models are only as effective as the data they’re trained with – if that data is insufficient, inaccurate, or biased, the model’s calculations will be too.
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AI Is More Than a Model: Four Steps to Complete Workflow Success
Engineers are increasingly looking to successfully integrate AI into projects and applications while attempting to climb their own AI learning curve. To tackle AI, engineers start with wanting to understand
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Moving predictive maintenance from theory to practice
Philipp H. F. Wallner, Industry Manager, Industrial Automation & Machinery, MathWorks, discusses four common hurdles that need to be overcome before tapping into the benefits of
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MathWorks and Coursera offer courses to bridge data skills gap
MathWorks and Coursera have launched a series of courses in a joint effort to address the data science skills gap across industries.
MathWorks is developing a series of courses entitled “Practical
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MathWorks announces Release 2019b of MATLAB and Simulink
MathWorks has released a range of new capabilities in MATLAB and Simulink, including those in support of artificial intelligence, deep learning and the automotive industry. In addition, R2019b introduces
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