Kyosuke MoritainTowards AIRAG-based Job Search AssistantUse RAG to optimize your job search and job applicationMar 51Mar 51
Kyosuke MoritainTowards AISurvey on Retrieval Augmented Generation (RAG)RAG development so far and the futureFeb 291Feb 291
Kyosuke MoritaCounterfactual Explanations in ICML 2023Paper Notes of Counterfactual Explanations in ICML 2023Nov 15, 2023Nov 15, 2023
Kyosuke MoritainTowards Data ScienceCFXplorer: Counterfactual Explanation Generation Python PackageIntroduces a Python package for generating counterfactual explanations for tree-based algorithmsAug 17, 2023Aug 17, 2023
Kyosuke MoritainTowards Data ScienceThe deferred acceptance (DA) algorithm utilised in school choice with PythonHow do we make a stable match between students and schools?Aug 4, 20221Aug 4, 20221
Kyosuke MoritainTowards Data ScienceDeep learning vs GBDT model on tabular data — with code snippetAn experiment of TabNet, MLP and XGBoost performance comparison on the home insurance data setMay 1, 2021May 1, 2021
Kyosuke MoritainTowards Data ScienceIs Your Machine Learning Model Still Predicting Accurately?Use Direct Ratios for the measurement of the “model drift” — An example with Bitcoin priceApr 25, 2020Apr 25, 2020
Kyosuke MoritainTowards Data ScienceCan we perform NLP on unfamiliar (natural) languages?Is generating sentences in Bulgarian easier than actually understanding it?Mar 1, 20201Mar 1, 20201
Kyosuke MoritainTowards Data ScienceProbability Calibration for Imbalanced DatasetA suggestion to Undersampling methodNov 18, 20192Nov 18, 20192
Kyosuke MoritainTowards Data ScienceNGBoost Explained— Comparison to LightGBM and XGBoostStanford ML Group recently published a new algorithm in their paper, (Duan et al., 2019) and its implementation called NGBoost. This…Oct 27, 20195Oct 27, 20195