Pinned Repositories
rtg-networks
EEG-ADHD-Project
In this research, we utilized data from a study that collected EEG data from 41 five-month-old infants with ADHD and 41 infants without ADHD with similar demographic information. The goal of the study is to create an optimal predictive model to identify which parts of the brain contribute heavily to the development of ADHD. Techniques: Data Processing, Logistic Regression, Elastic Net Regression, Random Forest, Cross Validation, Boostrapping, Parameter Tuning
36315-data-visualization-project
36315-Interactive-Graphs
36350
airbnb_Prediction
deep-learning-project
repo_A_test
repo_B_test
ROCK-MUSIC-GENERATION