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Transformer models like GPT-4 and BERT power key NLP tasks, excelling in context understanding and text generation.
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CNNs lead in computer vision, with Vision Transformers gaining traction in specific tasks.
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RNNs, including LSTM and GRU, are vital for time-series forecasting and speech recognition.
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KNN is a simple, effective algorithm used for classification and regression, favored for quick, accurate predictions in 2024.
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Random Forest is an ensemble algorithm excelling in classification, regression, and predictive tasks.
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SVMs are popular for classification tasks in 2024, excelling in image recognition, bioinformatics, and text categorization.
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K-Means Clustering is key for unsupervised learning, used in customer segmentation and market analysis in 2024.
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GBMs like XGBoost and LightGBM excel in predictive tasks, widely used in finance and healthcare for accuracy and precision in 2024.
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Reinforcement Learning (RL) algorithms, such as DQN and PPO, excel in robotics, healthcare, and dynamic applications.
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Neural Architecture Search (NAS) automates neural network design, optimizing models for various tasks in 2024.