深度学习
（王维语）CS3242024春 2023春2024春 2023春
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| 选课类别：课内实验 | 教学语言：英文 |
| 课程类别：专业选修课 | 开课单位：计算机科学与工程系 |
| 课程层次：未知 | 获得学分：3.0 |
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课程简介（教工部数据）
This course provides an introduction to the field of deep learning, covering the main deep learning techniques from both a theoretical and practical point of view. Architectures that will be covered include Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Autoencoders, and Generative Adversarial Networks (GANs) The goal of the course is that of equipping students with the necessary skills to access the rapidly evolving field of deep learning. To this end lectures and labs will draw multiple links to both the Industry and state-of-the-art academic research, allowing the students to pursue a successful career in both directions. The practical elements of the course will be based on the PyTorch framework, a widely used open source Python framework for deep learning.
This course provides an introduction to the field of deep learning, covering the main deep learning techniques from both a theoretical and practical point of view. Architectures that will be covered include Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Autoencoders, and Generative Adversarial Networks (GANs) The goal of the course is that of equipping students with the necessary skills to access the rapidly evolving field of deep learning. To this end lectures and labs will draw multiple links to both the Industry and state-of-the-art academic research, allowing the students to pursue a successful career in both directions. The practical elements of the course will be based on the PyTorch framework, a widely used open source Python framework for deep learning.
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