ADVANCED TOPICS IN DEEP LEARNING AND NEURAL NETWORKS
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Pay NowPublished Date: 2024-07-06
Author Name: Ms. Nitika Kadam Mr. Vikalp ThapliyalMs. Deepti Verma Ms. Rekha Yadav
Advanced topics in deep learning and neural networks include cutting-edge techniques like Generative Adversarial Networks (GANs), which generate realistic data samples through a dual-network competition, and reinforcement learning (RL), where models learn optimal behaviors via reward systems, excelling in applications like robotics and autonomous systems. Transformer architectures, exemplified by models such as BERT and GPT, have revolutionized natural language processing, enabling superior performance in tasks like translation and text generation. Other advanced areas include meta-learning, which focuses on models that learn how to learn, and neural architecture search (NAS), which automates the design of optimal neural network structures. These advancements collectively push the capabilities of AI, opening new possibilities in various domains, from healthcare to autonomous systems.