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This course provides an in-depth understanding of artificial intelligence (AI) models and networks, focusing on the principles, architectures, and applications of various AI models. Participants will learn about neural networks, deep learning, and the fundamentals of training and evaluating AI models. The course covers topics such as perceptrons, feedforward neural networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative models, and transfer learning.
Designing the user interface
Choosing the right technology stack
Implementing features and functionalities
Troubleshooting and debugging
Performance optimization
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