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Hyperparameter tuning also known as hyperparameter optimization is an important step in any machine learning model training that directly affects model performance.

This article covers two very popular hyperparameter tuning techniques: grid search and random search and shows how to combine these two algorithms with coarse-to-fine tuning.

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Survival analysis is a popular statistical method to investigate the expected duration of time until an event of interest occurs. We can recall it from medicine as patients' survival time analysis, from engineering as reliability analysis or time-to-failure analysis, and from economics as duration analysis.

Besides these disciplines, survival analysis…

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Regression models are widely used machine learning tools allowing us to make predictions from data by learning the relationship between features and continuous-valued outcomes. Checking model assumptions and understanding whether they are satisfied or not is as important as checking the accuracy and goodness of the model.

In this article…

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Creating “language-aware data products” are becoming more and more important for businesses and organizations. Leveraging on machine learning and NLP, organizations can interact with their customers both rationally and emotionally, improve their customer experience, and provide tailored assistance.

Although text is unstructured data and it is generally produced by people…

Idil Ismiguzel

Data Scientist | writing on Data Science & Machine Learning

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