XGBoost triggered the rise of the tree based models in the machine learning world. It earns reputation with its robust … More
Author: Sefik Serengil
A Gentle Introduction to XGBoost for Applied Machine Learning
XGBoost is firstly introduced in 2016 by Washington University Professors Tianqi Chen and Carlos Guestrin. Even though XGBoost appears in an … More
Artistic Style Transfer for Videos
State-of-the-art states the highest level in English. Because art is outpouring of human intelligence and sense of aesthetics. Artistic style transfer is … More
Mish As Neural Networks Activation Function
Recently, Mish activation function is announced in deep learning world. Researchers report that it overperforms than both regular ReLU and Swish. The … More
The Fastest Way to Calculate Combination and Permutation
Combination and permutation calculations appear often in daily programming challenges such as HackerRank. Even though we all know how to … More
Interpretable Machine Learning with H2O and SHAP
Previously, we’ve made explanations for h2o.ai models with lime. Lime enables questioning for made predictions of built models. Herein, SHAP … More
Explaining h2o models with Lime
Interpretability and accuracy inversely proportional concepts. Models offering higher accuracy such as deep learning or GBM would be lowly interpretable. … More
A Gentle Introduction to H2O GBM
GBM dominates tabular data based kaggle challenges. Putting it in the tool box is a must for data scientist. XGBoost, LightGBM … More
H2O Frame: Calling Forth The Power of Ten Tigers
Pandas has the power of a tiger. Its performance can still surprise me. However, it comes with a huge shortage. … More
Tips for Building AutoML with AutoKeras
Previously, we’ve already mentioned AutoKeras – an AutoML tool supported by Keras team. It just handles image data in a … More
