Welcome to Volume 2, Issue 1 of Advances in Deep Learning Techniques, where we continue our exploration of the dynamic field of deep learning research. In this edition, we present two groundbreaking papers that shed light on essential aspects of deep learning innovation. "Attention Mechanisms in Deep Learning" delves into attention mechanisms within deep learning models and their versatile applications across domains such as natural language processing. Simultaneously, "Adversarial Training Techniques in Deep Learning" investigates adversarial training techniques aimed at fortifying the robustness of deep learning models against adversarial attacks. Join us as we delve into the intricacies of deep learning, fostering innovation and resilience in artificial intelligence and machine learning systems.