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Neural Networks:


Neural networks are a key component of machine learning, inspired by the structure of the human brain. They consist of layers of interconnected nodes (neurons) that process and transmit information. Deep learning, a subset of machine learning, employs deep neural networks with multiple hidden layers to model complex patterns in data. Neural networks are fundamental to tasks like image recognition, natural language processing, and game playing, driving advancements in AI research and development.

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Machine Learning (ML):

 Machine learning is a subset of artificial intelligence (AI) that enables computers to learn from data and improve their performance over time without being explicitly programmed. ML algorithms identify patterns in large datasets and use these patterns to make predictions or decisions. Applications of machine learning include recommendation systems, fraud detection, and predictive analytics. It typically involves supervised, unsupervised, and reinforcement learning techniques.

Language Translation:

Language translation refers to the process of converting text or speech from one language to another using AI and machine learning techniques. Neural Machine Translation (NMT) models, which use deep learning, have dramatically improved the accuracy of language translation, enabling real-time services like Google Translate. These systems not only translate words but also understand the context and nuances of language, resulting in more natural translations.