深度學習無處不在：它應用于智能手機相機、語音助手和自動駕駛汽車，甚至在發(fā)現蛋白質結構和圍棋比賽中擊敗人類方面發(fā)揮了重要作用。深度學習（Deep Learning, DL）是人工智能（Artificial Intelligence, AI）的核心內容，是面向大學三年級學生開設的一門專業(yè)核心課程，旨在為學生構建深度學習領域的扎實基礎。它強調培養(yǎng)學生的深度學習思維和實踐能力，使學生能夠深入理解深度學習的基本原理、算法和應用。通過學習這門課程，學生將掌握神經網絡、卷積神經網絡、循環(huán)神經網絡等核心技術，并學會運用這些技術解決實際問題。課程的知識領域涵蓋了深度學習的各個方面，包括神經網絡基礎、深度學習框架、優(yōu)化算法、正則化方法、深度學習應用等。課程的主要內容包括但不限于：神經網絡的構建與訓練、深度學習模型的優(yōu)化與評估、深度學習在計算機視覺、自然語言處理等領域的應用等。課程不僅在于傳授理論知識，還包含培養(yǎng)學生的創(chuàng)新能力和實踐能力。通過這門課程的學習，學生將能夠運用深度學習技術解決實際問題，并學習如何使用最受歡迎的深度學習框架PyTorch進行項目實踐，為未來的科研和職業(yè)發(fā)展打下堅實的基礎。 |
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Deep learning is everywhere: in smartphone cameras, voice assistants, and self-driving cars. It has even helped discover protein structures and beat humans at the game of Go. Deep Learning (DL) is a core component of Artificial Intelligence (AI), and a professional core course for third-year college students, aiming at building a solid foundation for students in the field of deep learning. It emphasizes the cultivation of students' deep learning thinking and practical ability, so that students can deeply understand the basic principles, algorithms and applications of deep learning. By studying this course, students will master the core technologies such as neural network, convolutional neural network and cyclic neural network, and learn to use these technologies to solve practical problems. The knowledge field of the course covers all aspects of deep learning, including neural network foundation, deep learning framework, optimization algorithm, regularization method, deep learning application and so on. The main contents of the course include but are not limited to: the construction and training of neural networks, the optimization and evaluation of deep learning models, and the application of deep learning in computer vision, natural language processing and other fields. The course is not only to impart theoretical knowledge, but also to cultivate students' innovative ability and practical ability. Through this course, students will be able to apply deep learning techniques to solve real-world problems and learn how to use PyTorch, one of the most popular deep learning frameworks, for practical projects. This will lay a solid foundation for future research and career development. |
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