Full Description
This comprehensive textbook offers a unique approach to learning machine learning and deep learning by seamlessly integrating theoretical foundations with hands-on laboratory exercises. The book bridges the gap between theory and practice, providing students and practitioners with both the conceptual understanding and practical implementation skills necessary in today's AI landscape.
Each chapter follows a carefully structured format that combines theoretical explanations with immediate practical applications. This innovative approach allows readers to reinforce their understanding through direct implementation, creating a more engaging and effective learning experience.
Contents
Deep learning basics.- Convolutional Neural Networks.- Recurrent Neural Networks.- Attention Mechanisms, Transformers and LLMs.
