{"id":4652,"date":"2024-04-18T18:43:54","date_gmt":"2024-04-19T01:43:54","guid":{"rendered":"https:\/\/blog.sociamonials.com\/glossary\/fine-tuning-deep-learning\/"},"modified":"2024-04-18T18:43:54","modified_gmt":"2024-04-19T01:43:54","slug":"fine-tuning-deep-learning","status":"publish","type":"glossary","link":"https:\/\/blog.sociamonials.com\/es\/glossary\/ajuste-del-aprendizaje-profundo\/","title":{"rendered":"Ajuste fino (aprendizaje profundo)"},"content":{"rendered":"

Fine-tuning, a technique utilized in deep learning within the realm of artificial intelligence<\/a>[1]<\/a><\/sup><\/span>, specifically pertains to machine learning algorithms. It primarily serves to boost the efficacy of existing neural network models by modifying and repurposing specific parameters within these models. This method is a subset of transfer learning, wherein insights obtained from one task are leveraged for another related task. Fine-tuning can be implemented across the entire network or a selected group of layers, often incorporating adapters for enhancement. It proves particularly beneficial in natural language processing for language modeling. Nonetheless, it’s crucial to acknowledge that fine-tuning can occasionally impact a model’s stability, necessitating techniques like linear interpolation to maintain performance. Various strategies, such as the Low-rank adaptation (LoRA) method, present alternative ways to fine-tune.<\/p>\n

Terms definitions<\/div>
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1. <\/span> ↑ <\/a><\/span> artificial intelligence<\/a>. <\/span> The discipline of Artificial Intelligence (AI) is a subset of computer science dedicated to developing systems capable of executing tasks usually requiring human intellect, such as reasoning, learning, planning, perception, and language comprehension. Drawing upon diverse fields such as psychology, linguistics, philosophy, and neuroscience, AI is instrumental in the creation of machine learning models and natural language processing systems. It also significantly contributes to the development of virtual assistants and affective computing systems. AI finds applications in numerous sectors like healthcare, industry, government, and education. However, it also brings up ethical and societal issues, thus requiring regulatory policies. With the advent of sophisticated techniques like deep learning and generative AI, the field continues to expand, opening up new avenues in various sectors. <\/span><\/div><\/div>
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Fine-tuning, a technique utilized in deep learning within the realm of artificial intelligence, specifically pertains to machine learning algorithms. It primarily serves to boost the efficacy of existing neural network models by modifying and repurposing specific parameters within these models. This method is a subset of transfer learning, wherein insights obtained from one task are […]<\/p>\n

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Terms definitions<\/div>\n
<\/div>\n
1. <\/span> ↑ <\/a><\/span> artificial intelligence<\/a>. <\/span> The discipline of Artificial Intelligence (AI) is a subset of computer science dedicated to developing systems capable of executing tasks usually requiring human intellect, such as reasoning, learning, planning, perception, and language comprehension. Drawing upon diverse fields such as psychology, linguistics, philosophy, and neuroscience, AI is instrumental in the creation of machine learning models and natural language processing systems. It also significantly contributes to the development of virtual assistants and affective computing systems. AI finds applications in numerous sectors like healthcare, industry, government, and education. However, it also brings up ethical and societal issues, thus requiring regulatory policies. With the advent of sophisticated techniques like deep learning and generative AI, the field continues to expand, opening up new avenues in various sectors. <\/span><\/div>\n<\/div>\n
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Terms definitions<\/div>
<\/div>
1. <\/span> ↑ <\/a><\/span> artificial intelligence<\/a>. <\/span> The discipline of Artificial Intelligence (AI) is a subset of computer science dedicated to developing systems capable of executing tasks usually requiring human intellect, such as reasoning, learning, planning, perception, and language comprehension. Drawing upon diverse fields such as psychology, linguistics, philosophy, and neuroscience, AI is instrumental in the creation of machine learning models and natural language processing systems. It also significantly contributes to the development of virtual assistants and affective computing systems. AI finds applications in numerous sectors like healthcare, industry, government, and education. However, it also brings up ethical and societal issues, thus requiring regulatory policies. With the advent of sophisticated techniques like deep learning and generative AI, the field continues to expand, opening up new avenues in various sectors. <\/span><\/div><\/div>
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