Lidet TeferaAnalysis of‘BinaryConnect: Training Deep Neural Networks with binary weights during propagations’The study titled ‘BinaryConnect: Training Deep Neural Networks with binary weights during propagations’ by Courbariaux, Bengio and David…Aug 24, 2020Aug 24, 2020
Lidet TeferaDistilling the Knowledge in a Neural NetworkIn the paper titled ‘Distilling the Knowledge in a Neural Network’ by Hinton, Vinyals and Dean discuss how a knowledge acquired from a…Aug 17, 2020Aug 17, 2020
Lidet TeferaPrinciple Component AnalysisPrinciple Component Analysis (PCA) is a feature extraction technique. The technique emphasizes variation and highlights strong patterns in…Jul 27, 2020Jul 27, 2020
Lidet TeferaCurse of DimensionalityAlthough a large dataset is often beneficial for the performance of a machine learning model, it can sometimes present a problem. A higher…Jul 19, 2020Jul 19, 2020
Lidet TeferaClusteringThe main idea behind clustering is that you want to group objects into similar classes, in a way that:Jul 13, 2020Jul 13, 2020
Lidet TeferaPrecision and recallPrecision and Recall are two of the most basic evaluation metrics available to us. Precision measures how precise the predictions are…Jul 5, 2020Jul 5, 2020
Lidet Teferak-Fold Cross-ValidationK-Fold Validation is resampling procedure used to evaluate machine learning models on a limited data sample. In k-fold cross-validation…Jun 27, 2020Jun 27, 2020
Lidet TeferaClass ImbalancesMeasuring the performance of classification algorithms is substantially different from that of regression. For example, in a scenario…Jun 21, 2020Jun 21, 2020
Lidet TeferaSupport Vector MachineA support vector machine (also referred to as SVMs) is a supervised machine learning model that uses classification algorithms for…Jun 16, 2020Jun 16, 2020