Federated Learning
Training across decentralized devices
- Federated Learning enables collaborative model training without sharing raw data, preserving privacy.
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LightGBM
Efficient gradient boosting
- LightGBM is a gradient boosting framework optimized for speed and memory efficiency.
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Edge AI
AI on local devices
- Edge AI runs AI models on devices like smartphones and IoT sensors, reducing latency and improving privacy.
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Backpropagation
Training neural networks
- Backpropagation is an algorithm for updating weights in neural networks by propagating errors backward through the layers.
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Cloud AI
AI services on cloud platforms
- Cloud AI provides scalable AI solutions through cloud infrastructure, enabling easy deployment and management.
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Overfitting
Model fits training data too well
- Overfitting occurs when a model learns noise in the training data, reducing its ability to generalize to new data.
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Big Data
Large-scale data processing
- Big Data refers to datasets too large for traditional processing, requiring specialized tools and techniques.
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Underfitting
Model fails to capture patterns
- Underfitting happens when a model is too simple to learn the underlying structure of the data.
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Data Mining
Extracting patterns from data
- Data Mining involves discovering patterns and relationships in large datasets for decision-making.
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