Interview Kickstart today announces the publication of its comprehensive career guide titled "How to Transition from Software Engineer to Machine Learning Engineer," a detailed resource created to ...
17don MSN
Automating microfluidic chip design: Hybrid approach combines machine learning with fluid mechanics
Researchers led by Assoc. Prof. Dr. Savaş Taşoğlu from the Department of Mechanical Engineering at Koç University have ...
Materials with advanced customized properties drive innovation in a number of real-life applications across various fields, such as information technology, transportation, green energy and health ...
Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...
Microelectromechanical systems (MEMS) electrothermal actuators are widely used in applications ranging from micro-optics and microfluidics to nanomaterial testing, thanks to their compact size and ...
Why it’s important not to over-engineer. Equipped with suitable hardware, IDEs, development tools and kits, frameworks, datasets, and open-source models, engineers can develop ML/AI-enabled, ...
Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...
What if the skills you choose to learn today could determine your career trajectory in 2025? The field of machine learning is evolving at a breakneck pace, and with it comes a growing demand for ...
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