t-SNE, the Ultimate Drum Machine and more

This blog explains t-SNE (t-Distributed Stochastic Neighbor Embedding) by a story of programmers joining forces with musicians to create the ultimate drum machine (if you are here just for the fun, you may start playing right away). Kyle McDonald, Manny Tan, and Yotam Mann experienced difficulties in pinpointing to what extent sounds are similar (ding, dong) … Continue reading t-SNE, the Ultimate Drum Machine and more

Light GBM vs. XGBOOST in Python

XGBOOST stands for eXtreme Gradient Boosting. A big brother of the earlier ADABOOST, XGB is a supervised learning algorithm that uses an ensemble of adaptively boosted decision trees. For those unfamiliar with adaptive boosting algorithms, here's a 2-minute explanation video and a written tutorial. Altough XGBOOST often performs well in predictive tasks, the training process can … Continue reading Light GBM vs. XGBOOST in Python

Keras: Deep Learning in R or Python within 30 seconds

Keras is a high-level neural networks API that was developed to enabling fast experimentation with Deep Learning in both Python and R. According to its author Taylor Arnold: Being able to go from idea to result with the least possible delay is key to doing good research. The ideas behind deep learning are simple, so … Continue reading Keras: Deep Learning in R or Python within 30 seconds