Content and Features of This Book • Applied Mathematics (15 questions) Organizes the mathematical foundations of AI/ML, including probability, statistics, linear algebra, and optimization theory. • Machine Learning (25 questions) Systematically covers regression, classification, SVM, ensemble learning, regularization, evaluation metrics, and more. • Deep Learning (45 questions) Completely covers major models such as CNN, RNN, LSTM, Transformer, GAN, and Attention. • Development and Operational Environment (15 questions) Confirms practical skills in TensorFlow, PyTorch, Git, Docker, Kubernetes, CI/CD, and more. • Detailed explanations for all questions Provides detailed explanations not only for why the answer is correct but also for why the incorrect options are wrong. --- ✅ Includes a total of 100 questions covering the entire scope, along with detailed answers and explanations. ✅ Addresses the latest AI topics (Transformer, Generative AI, cloud implementation).