Delves into Big Data in neuroscience, analyzing large datasets and addressing challenges in data organization, standardization, integration, and visualization.
Explores text mining of long-tail data in neuroscience and brain connectivity, including named entity recognition, protein concentration mining, and comparison of connectivity matrices.
Covers ensemble methods like random forests and Gaussian Naive Bayes, explaining how they improve prediction accuracy and estimate conditional Gaussian distributions.
