scutan90/deeplearning-500-questions

DeepLearning-500-questions is a Chinese-language study guide and interview preparation resource for deep learning and machine learning. The title translates roughly to "500 Questions in Deep Learning," and the format is a structured question-and-answer collection covering topics that commonly appear in job interviews and academic examinations at Chinese technology companies. The README indicates this content has also been published as a physical book available through Chinese booksellers. The resource is organized into 14 chapters covering mathematical foundations (probability, linear algebra, calculus), classical machine learning concepts (supervised learning, decision trees, support vector machines, clustering), deep learning fundamentals (neural network architectures, activation functions, batch normalization, regularization), specific neural network types (convolutional networks for image processing, recurrent networks, generative adversarial networks), and computer vision applications including object detection and image segmentation. Later chapters cover practical topics like transfer learning, hyperparameter tuning, and model compression. The depth of treatment ranges from conceptual explanations with diagrams to worked mathematical derivations. The README is written entirely in Chinese and the content throughout is in Chinese, making it specifically aimed at Mandarin-speaking students and practitioners. The repository is listed as ongoing, with more content indicated as forthcoming. You would use this resource when preparing for machine learning or deep learning job interviews at Chinese tech companies, studying for graduate school entrance examinations in AI-related fields, or as a systematic review companion to an academic deep learning course.