Kyosuke MoritainTowards AIRAG-based Job Search AssistantUse RAG to optimize your job search and job application·10 min read·Mar 5, 2024--1--1
Kyosuke MoritainTowards AISurvey on Retrieval Augmented Generation (RAG)RAG development so far and the future·21 min read·Feb 29, 2024--1--1
Kyosuke MoritaCounterfactual Explanations in ICML 2023Paper Notes of Counterfactual Explanations in ICML 202311 min read·Nov 15, 2023----
Kyosuke MoritainTowards Data ScienceCFXplorer: Counterfactual Explanation Generation Python PackageIntroduces a Python package for generating counterfactual explanations for tree-based algorithms·9 min read·Aug 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?·7 min read·Aug 4, 2022--1--1
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 set·8 min read·May 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 price·9 min read·Apr 25, 2020----
Kyosuke MoritainTowards Data ScienceCan we perform NLP on unfamiliar (natural) languages?Is generating sentences in Bulgarian easier than actually understanding it?·13 min read·Mar 1, 2020--1--1
Kyosuke MoritainTowards Data ScienceProbability Calibration for Imbalanced DatasetA suggestion to Undersampling method·8 min read·Nov 18, 2019--2--2
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…·5 min read·Oct 27, 2019--5--5