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CSE 253: Neural Networks for Pattern Recognition Winter 2020 Syllabus TT: 9:3010:50 Price Center Theater Professor: Gary Cantrell Office: CSE 4130; Phone: 8585346640 Garys Office hours: To be announced
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CSE 253 Neural Networks is likely a course or module that focuses on the theoretical and practical aspects of neural networks, including their architectures, training methods, and applications in machine learning.
Typically, individuals enrolled in the course or those involved in projects related to neural networks may be required to submit assignments or projects pertaining to CSE 253.
To fill out assignments for CSE 253, students generally need to follow the guidelines provided by the instructor, which may include structuring their work according to specified formats, submitting programming projects, and providing appropriate documentation.
The purpose of CSE 253 Neural Networks is to educate students about neural network models, their functionalities, and how to implement them for various applications in fields such as artificial intelligence and data science.
Students may need to report information such as project objectives, methodology, results, and code implementations as part of their coursework in CSE 253.
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