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Michio Inoue's Projects

arrange-resize-figures icon arrange-resize-figures

The script resizes the MATLAB figures and arranges them in a grid on the monitor. These figures can be exported in PDF format. The exported figures conforms to IEEE format as default.

calling-cotoha-api-from-matlab icon calling-cotoha-api-from-matlab

This repo provides some examples of calling COTOHA API from MATLAB. COTOHA API is developed by NTT group with service natural language processing. For details, see https://api.ce-cotoha.com/contents/index.html

classical-music-composers-classification icon classical-music-composers-classification

This contribution provides the code to train the winning model (2nd place) of the competition "Classical music composers classification" (https://www.nishika.com/competitions/8/summary)

electrophysiology-tutorial-for-neuroscience_jp icon electrophysiology-tutorial-for-neuroscience_jp

This repository contains a Japanese version of a published repository "Electrophysiology tutorial for neuroscience" by Shubo Chakrabarti https://github.com/mathworks/Electrophysiology-Tutorial-for-Neuroscience

livescript2markdown icon livescript2markdown

MATLAB's live scripts to markdown. The provided function converts your latex (generated from a live script) to markdown so that it could easily produce README.md with MATLAB code, equations, and figures.

math-algorithm-book icon math-algorithm-book

拙著『「アルゴリズム×数学」が基礎からしっかり身につく本』(12/25 発売予定)の GitHub ページです。演習問題の解答や、C++ 以外のソースコードなどが掲載されています。ぜひご活用ください。

matlab-gan icon matlab-gan

MATLAB implementations of Generative Adversarial Networks -- from GAN to Pixel2Pixel, CycleGAN

nlp-100-exercise-by-matlab icon nlp-100-exercise-by-matlab

This repo provides MATLAB examples for NLP 100 Exercise, which was developed by Prof. Naoaki Okazaki in 2011-2012 for the use in a study group for programming. See https://github.com/taku-ito/nlp100.github.io

practical-statistics-for-data-scientists-with-matlab icon practical-statistics-for-data-scientists-with-matlab

This repository provides MATLAB code for the computation described in the book "Statistics for Data Scientists: 50 Essential Concepts." Original R code and data can be found here. https://github.com/andrewgbruce/statistics-for-data-scientists

predict-rul-of-airplane-turbofan-engine icon predict-rul-of-airplane-turbofan-engine

This contribution provides the code to train the winning model (1st place) of the competition " Predict RUL of Airplane Turbofan Engine" (https://www.nishika.com/competitions/17/summary)

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