Grad-CAM: Visual Explanations from Deep Networks
Genomics, Transcriptomics, and Proteomics for Data Scientists (DNA, RNA, Protein)
Squeeze-and-Excitation Networks
Machine Learning, Medicine, radiology
Automatic Interpretation of Chest CT Scans with Machine Learning
Multi-GPU Training in Pytorch: Data and Model Parallelism
Comparing AUCs of Machine Learning Models with DeLong’s Test
Segmentation: U-Net, Mask R-CNN, and Medical Applications
Connections: Log Likelihood, Cross Entropy, KL Divergence, Logistic Regression, and Neural Networks
