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Machine Learning, 10-701 and 15-781, 2003

It is hard to imagine anything more fascinating than automated systems that improve their own performance. The study of learning from data is commercially and scientifically important. This course is ...
Frontiers

Machine learning approaches for cardiovascular hypertension stage estimation using photoplethysmography and clinical features

Cardiovascular diseases (CVDs) are a leading cause of death worldwide, with hypertension emerging as a significant risk factor. Early detection and treatment of hypertension can significantly reduce ...
GitHub

yifeipet/transferlearning-MMD-using-Numpy-and-Sklearn-

@Misc{transferlearning.xyz, howpublished = {\url{http://transferlearning.xyz}}, title = {Everything about Transfer Learning and Domain Adapation}, author = {Wang ...
PNAS

Learning nonnative speech sounds changes local encoding in the adult human cortex

Speech sound learning in adulthood is a highly dynamic process. Here, we used direct neurophysiology of the human brain to examine learning-associated changes in neural activity with unprecedented ...
GitHub

Model Zoo

Check out the model zoo documentation for details. 16-layer: 7.5% top-5 error on ILSVRC-2012-val, 7.4% top-5 error on ILSVRC-2012-test 19-layer: 7.5% top-5 error on ...
C&EN

Complex Chemical Data Classification and Discrimination Using Locality Preserving Partial Least Squares Discriminant Analysis

Partial least squares discriminant analysis (PLS-DA) is a well-known technique for feature extraction and discriminant analysis in chemometrics. Despite its popularity, it has been observed that ...
Nature

Deep learning is combined with massive-scale citizen science to improve large-scale image classification

Pattern recognition and classification of images are key challenges throughout the life sciences. We combined two approaches for large-scale classification of fluorescence microscopy images. First, ...