Skin-Cancer-SegmentationClassification and Segmentation with Mask-RCNN of Skin Cancer using ISIC dataset
Stars: ✭ 61 (+205%)
Mutual labels: classification
ugtmugtm: a Python package for Generative Topographic Mapping
Stars: ✭ 34 (+70%)
Mutual labels: classification
BIRADS classifierHigh-resolution breast cancer screening with multi-view deep convolutional neural networks
Stars: ✭ 122 (+510%)
Mutual labels: classification
textlearnRA simple collection of well working NLP models (Keras, H2O, StarSpace) tuned and benchmarked on a variety of datasets.
Stars: ✭ 16 (-20%)
Mutual labels: classification
R-Machine-LearningD-Lab's 6 hour introduction to machine learning in R. Learn the fundamentals of machine learning, regression, and classification, using tidymodels in R.
Stars: ✭ 27 (+35%)
Mutual labels: classification
verseagilityRamp up your custom natural language processing (NLP) task, allowing you to bring your own data, use your preferred frameworks and bring models into production.
Stars: ✭ 23 (+15%)
Mutual labels: classification
NN-scratchCoding up a Neural Network Classifier from Scratch
Stars: ✭ 78 (+290%)
Mutual labels: classification
flexinferA flexible Python front-end inference SDK based on TensorRT
Stars: ✭ 83 (+315%)
Mutual labels: classification
Machine-Learning-SpecializationProject work and Assignments for Machine learning specialization course on Coursera by University of washington
Stars: ✭ 27 (+35%)
Mutual labels: classification
TNCR DatasetDeep learning, Convolutional neural networks, Image processing, Document processing, Table detection, Page object detection, Table classification. https://www.sciencedirect.com/science/article/pii/S0925231221018142
Stars: ✭ 37 (+85%)
Mutual labels: classification
MoeFlowRepository for anime characters recognition website, powered by TensorFlow
Stars: ✭ 113 (+465%)
Mutual labels: classification
newtNatural World Tasks
Stars: ✭ 24 (+20%)
Mutual labels: classification
knodleA PyTorch-based open-source framework that provides methods for improving the weakly annotated data and allows researchers to efficiently develop and compare their own methods.
Stars: ✭ 76 (+280%)
Mutual labels: classification
Classification NetsImplement popular models by different DL framework. Such as tensorflow and caffe
Stars: ✭ 17 (-15%)
Mutual labels: classification