Benefits and Applications in ML
1
Big data consists of various components that work together to analyze vast datasets.
2
It addresses data scarcity, improves model robustness, and reduces overfitting by exposing models to diverse training scenarios.
3
– Geometric transformations (rotation, flipping) – Color adjustments – Synthetic data generation
4
– Increases dataset size – Improves accuracy – Saves costs on data collection – Enhances generalization
5
– Image classification – Object detection to improve model performance
6
– TensorFlow – Keras – PyTorch – Albumentations
7
Utilize data augmentation techniques today to enhance your Machine Learning models
data augmentation in machine learning