Niklas Lang

Understanding the Connections Between Variables: A Comprehensive Guide to Correlation Matrices and Their Applications Niklas Lang · Follow Published in Towards Data Science · 13 min read · 13 hours ago — Photo by ZENG YILI on Unsplash Data analysis is primarily used to identify and quantify correlations and patterns between variables so that they can be used for future predictions and corresponding models can be trained. The correlation matrix is a crucial method that

Learn how ARIMA models work and how to implement them in Python for accurate predictions Niklas Lang · Follow Published in Towards Data Science · 14 min read · 21 hours ago — Photo by Jean-Luc Picard on Unsplash The abbreviation ARIMA stands for AutoRegressive Integrated Moving Average and refers to a class of statistical models used to analyze time series data. This model can be used to make predictions about the future development of

A beginner’s guide to the architecture, Python implementation, and a glimpse into the future Niklas Lang · Follow Published in Towards Data Science · 19 min read · 9 hours ago — Photo by Clark Van Der Beken on Unsplash Autoencoders are a special form of deep neural networks primarily used for feature extraction or dimension reduction. As they can work with unlabeled data, they belong to the field of unsupervised learning. The architecture consists

An Introduction to Markov Chains, their applications, and how to use Monte Carlo Simulations in Python Niklas Lang · Follow Published in Towards Data Science · 10 min read · 12 hours ago — Photo by Kevin Oetiker on Unsplash The Markov chain is a central concept in mathematics and stochastics and is used to predict the probability of certain states in stochastic processes. The central feature of such systems is the so-called “memorylessness” since