In this Tools of the Trade article, Jordan Lee describes the development and use of the Tumor Molecular Pathology (TMP) toolkit, a cancer subtyping tool that can assign TCGA molecular subtypes to new, independent non-TCGA datasets.Jordan Lee...
8. Improvement of scoring functions can be achieved by developing new terms, training on larger high-quality datasets or using sophisticated machine learning-based
The easiest way to use Machine Learning. Mix and match underlying ML libraries and data set sources. Generate new datasets or modify existing ones with ease. - intel/dffml
WebVision and ImageNet datasets, and object detection task on KITTI dataset, learning a dynamic curriculum via data parameters leads to consistent gains, without any increase in model complexity or training time. When applied to a noisy dataset, the proposed method learns to learn from clean images...
learning modelling searches numerically for the best model, the forecasts are mostly much better than in classical theory- and user-feeling-driven approaches; and (c) due to data selection via boosting, sampling, bootstrapping, etc., the machine learning model can work with much bigger datasets...
Imbalanced datasets pose a serious challenge to classification problems because most of the machine learning algorithms used for classification are designed assuming an equal number of samples for each class (e.g. SVM: further details in Appendix A). In fact, since in this case, the probability ...
Added Advanced Training feature with a new machine learning backend for improved performance, especially on challenging datasets and fine-grained classification. With advanced training, you can specify a compute time budget for training and Custom Vision will experimentally identify the best training and ...
The machine learning-based geological mapping incorporates geo-exploratory datasets, which consist of labeled geological units, geochemical data capturing concentrations of 15 trace elements at various sampling locations, and remote sensing data encompassing ASTER and Landsat 8 OLI data. The current ...
effective algorithm and briefly analyze why our method works better than TNN based methods in the case of complex data with low sampling rate. Finally, experimental results on real-world datasets demonstrate the superiority of our proposed models in the tensor completion problem with respect to ...
Promising drone-delivery startup is hiring a Dataset and Machine Learning Manager to work remotely. OneSec is working on a groundbreaking GPT-scale machine learning project to make autonomous delivery drones. In this job, you will build the Datasets and Neural Networks that fly our autonomous deli...