Explaining Deep Learning and Convolutional Neural Network (CNN) with a Practical Example
Artificial intelligence (AI) encompasses a broad area within computer science and has extensive applications across various fields, including mechanical engineering. AI involves endowing machines with intelligence, empowering them to perform tasks that typically require human cognition. Moreover, to analyze stress distribution in components, the Finite Element Method (FEM) is employed. In this video, I will introduce the foundational concepts of Artificial Intelligence (AI), Machine Learning (ML), Artificial Neural Networks, Deep Learning (DL), and particularly the Convolutional Neural Network (CNN) methodology through a practical example. I aim to demonstrate how deep learning and the CNN approach can be utilized to predict the stress distribution in a component.
Join us to improve your skills in the new concept of simulation using Deep learning and the CNN approach and feel free to share your thoughts in the comments below. Don't forget to like and subscribe for more insights!
If you have any inquiries or need the PowerPoint file, please do not hesitate to contact us.
E-mail address: precision.manufacturing22@gmail.com
#artificialintelligence #cnn #Convlutionalneuralnetwork #abaqustutorial #stress #deeplearning #machinelearning #ai #ml #artificialneuralnetwork #python #abaqus #cae #prediction
Artificial intelligence (AI) encompasses a broad area within computer science and has extensive applications across various fields, including mechanical engineering. AI involves endowing machines with intelligence, empowering them to perform tasks that typically require human cognition. Moreover, to analyze stress distribution in components, the Finite Element Method (FEM) is employed. In this video, I will introduce the foundational concepts of Artificial Intelligence (AI), Machine Learning (ML), Artificial Neural Networks, Deep Learning (DL), and particularly the Convolutional Neural Network (CNN) methodology through a practical example. I aim to demonstrate how deep learning and the CNN approach can be utilized to predict the stress distribution in a component.
Join us to improve your skills in the new concept of simulation using Deep learning and the CNN approach and feel free to share your thoughts in the comments below. Don’t forget to like and subscribe for more insights!
If you have any inquiries or need the PowerPoint file, please do not hesitate to contact us.
E-mail address: precision.manufacturing22@gmail.com
#artificialintelligence #cnn #Convlutionalneuralnetwork #abaqustutorial #stress #deeplearning #machinelearning #ai #ml #artificialneuralnetwork #python #abaqus #cae #prediction
