Hyperparameter Tuning of a Random Forest Classifier using Grid Search in Python

The functionality of machine learning models can be controlled with their hyperparameters. The choice of these parameters often has a significant impact on model performance and, in practice, can make the difference between sufficient and outstanding performance. Data scientists therefore … Continued

Feature Engineering for Multivariate Time Series Prediction with Python

Multivariate time series predictions and especially stock market forecasts pose challenging machine learning problems. Unlike univariate forecasting models, multivariate models do not rely exclusively on historical time series data, but use additional functions that are often developed from the time … Continued

Simple Sentiment Analysis using Naive Bayes and Logistic Regression

Sentiment Analysis refers to the use of Machine Learning and Natural Language Processing (NLP) to systematically detect emotions in text. In recent years, sentiment analysis found broad adoption across industries. One reason for its popularity is, that it is increasingly … Continued

Building Multivariate Time Series Models for Stock Market Prediction with Python

Time series prediction has become a major domain for the application of machine learning and more specifically recurrent neural networks. Well-designed multivariate prediction models are now able to recognize patterns in large amounts of data, allowing them to make more … Continued

Will they Buy or just Browse? Predicting Purchase Intentions of Online Shoppers with Python

Many online stores welcome countless visitors every day, but only a fraction of those visitors will actually make a purchase. In this blog, I show how you can use machine learning to predict whether a customer is just browsing the … Continued

Evaluate Time Series Forecasting Models with Python

Time series forecasting models Evaluating the performance of forecasting models is important and a crucial step in their development. This is especially the case for time series forecasting models. Compared to classification models, time series predictions cannot easily be divided … Continued