Hyperparameter Tuning with Grid Search at the Example of a Random Forest Classifier with 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 shops welcome countless visitors each day. However, only a fraction of these visitors will actually make a purchase. The rest just browses through the websites and does not make a transaction. This blog post is dedicated to the … Continued

Building a Simple Univariate Model for Stock Market Prediction using Keras Recurrent Neural Networks and Python

Stock market prediction: a time series forecasting problem Forecasting the price of financial assets has fascinated researchers and analysts for many decades. While traditional prediction methods of technical analysis and fundamental analysis are still widely used, interest is now increasingly … Continued