Abstract
Abstract: Machine learning and deep learning have been widely embraced, and even more widely misunderstood. In this article, I’d like to step back and explain both machine learning and deep learning in basic terms, discuss some of the most common machine learning algorithms, and explain how those algorithms relate to the other pieces of the puzzle of creating predictive models from historical data. As a discipline, machine learning explores the analysis and construction of algorithms that can learn from and make predictions on data.ML has proven valuable because it can solve problems at a speed and scale that cannot be duplicated by the human mind alone. With massive amounts of computational ability behind a single task or multiple specific tasks, mac Shines can be trained to identify patterns in and relationships between input data and automate routine processes Keywords: Random Forest algorithm, Logistic Regression, Long short-term Memory, ROC curves evaluation
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