VECTOR | [3-0-0:3] |
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DESCRIPTION | In the era of large-scale deep learning models, multimodal learning based on speech, text, and images is gaining increasing prominence. It holds the potential to facilitate cross-domain applications, improve human-computer interaction, and advance innovation in the field of AI. This course will provide an in-depth exploration of applied deep learning techniques, focusing on their applications in speech processing, natural language understanding, and multimodal data analysis. Students will gain practical experience in building deep learning models for various tasks, including speech recognition, language translation, image analysis, and more. The course covers fundamental concepts, algorithms, and tools in the field of deep learning and emphasizes hands-on projects and real-world applications. |
Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
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L01 (6215) | Tu 09:00AM - 11:50AM | Rm 233, W1 | LIU, Li | 40 | 12 | 28 | 0 |
VECTOR | [0 credit] |
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DESCRIPTION | Series of seminars presenting research problems currently under investigation, presented by faculty, students, and visiting speakers. Students are expected to attend regularly. Graded P or F. |
Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
---|---|---|---|---|---|---|---|---|
T01 (6057) | Th 11:00AM - 11:50AM | Rm 101, W1 | LIU, Li | 100 | 33 | 67 | 0 |
VECTOR | [0-1-0:1] |
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DESCRIPTION | Series of seminars presenting research problems currently under investigation, presented by faculty, students, and visiting speakers. Students are expected to attend regularly. Continuation of AIAA 6101. Graded P or F. |
Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
---|---|---|---|---|---|---|---|---|
T01 (6058) | Fr 11:00AM - 11:50AM | Rm 101, W1 | LIU, Li | 100 | 32 | 68 | 0 |