The advent of big data and machine learning has revolutionized epidemiology. Big data refers to extremely large datasets that traditional data processing software cannot handle. Machine learning involves algorithms that can learn from and make predictions on data. Together, they enable epidemiologists to analyze complex datasets, uncover patterns, and make data-driven decisions. Tools like Apache Hadoop and Spark are instrumental in managing big data, while libraries like scikit-learn and TensorFlow in Python facilitate machine learning applications.
