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Dataset augmentation for Deep Learning

Dataset augmentation for Deep Learning

Introduction Dataset augmentation for Deep Learning is the finest way to create a machine learning algorithm. The act of maximum Machine Learning models is influenced by the quantity and diversity of data. Most companies use data augmentation to decrease dependency on training data preparation. Data augmentation is a method for making data for machine learning … Read more

Ensemble methods in Deep Learning

Ensemble methods in Deep Learning

Introduction Ensemble methods in Deep Learning associate the output of machine learning models in various stimulating means. We were unmindful of the power of ensemble methods after years of working on machine learning projects. Because this topic is typically ignored or only given a short-lived outline in utmost machine learning courses and books. By testing … Read more

Overflow and Underflow in Deep Learning

Overflow and Underflow in Deep Learning

Introduction Deep learning algorithms generally need a high volume of numerical computation. This normally states to algorithms that solve mathematical problems. That is solved by methods to keep informed guesses of the solution through an iterative process. Somewhat than logically deriving a formula in case a symbolic expression for the correct solution. The general operations … Read more