Use of pipelines & randomized search to select the best classifier for a customer churn classification problem


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When working on a machine learning project, the preprocessing stage, which includes steps such as data cleaning, filling missing values, standardization or normalization, encoding the categorical variables, feature engineering etc., can be time consuming and susceptible to errors at cases where the dataset comprises a large number of features.


LSTM for Sequence-to-Sequence prediction using a Stock Market Dataset of three Input and one Target Time Series


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Time Series Forecasting

Time Series Forecasting is a method that aims to predict the future states of a variable based on its past observations, collected at specific time periods/intervals. Depending on the number of dataset features whose observations vary over time, Time Series can be distinguished into a) Univariate and b) Multivariate. …

Georgios Tourloukis

Data Scientist, PhD in Mathematical Modeling, MSc & BEng

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