Answer / Jayant Sachan

Smaller dataset techniques are used when dealing with limited data in machine learning. Some common techniques include: 1) Data Augmentation - generating new instances from existing data by applying random transformations like rotation, scaling, or flipping. 2) Transfer Learning - using pre-trained models and fine-tuning them on the smaller dataset. 3) Synthetic Data Generation - creating artificial data that resembles the original data distribution.

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