shinyfe74
HCI PhD / Python, Javascript, Php, Mysql. Email: minchulcha@minchulcha.com
Hankuk University of Foreign StudiesSeoul, Korea
Pinned Repositories
modality_selection
For test user's modality selection in multimodal system.
Ratio_Template_Matching
This code is for template matching when the template image has different size from original image.
Titanic_Prediction
Learn machine learning from Titanic disaster
Image_diversity
calculate image color diversity by fractal dimension using box-counting method
Image_harmony
calculate image color harmony by color hue degree
drag_n_drop_fitts_law
100-Days-of-DataScience
Greetings! ๐ I'm Loga Aswin, diving into a 100-day data science immersion from Python fundamentals to real-world applications. This space will be a live documentation of my journey, where code meets curiosity. Let's connect, learn, and code together. Click โญ on GitHub to stay tuned for updates on my work!
2021.ArtificialIntelligence
2021-2ํ๊ธฐ ์ง๋ฅ๊ธฐ์ ๊ณตํ๋ถ ์ธ๊ณต์ง๋ฅ์์
2022.AI
2022-2ํ๊ธฐ ์ง๋ฅ๊ธฐ์ ๊ณตํ๋ถ ์ธ๊ณต์ง๋ฅ ์์
2024.MachineLearning
2024๋ ๋ 1ํ๊ธฐ ๊ธฐ๊ณํ์ต ์์
shinyfe74's Repositories
shinyfe74/minchulcha.com
shinyfe74/2024.MachineLearning
2024๋ ๋ 1ํ๊ธฐ ๊ธฐ๊ณํ์ต ์์
shinyfe74/ML-Cheat-Codes
Machine Learning Cheatsheet 2024
shinyfe74/50-Days-OfCode-DeepLearning
shinyfe74/practical-statistics-for-data-scientists
Code repository for O'Reilly book
shinyfe74/God-Level-Data-Science-ML-Full-Stack
A collection of scientific methods, processes, algorithms, and systems to build stories & models. Whether you are a fresher in the field or an experienced professional who wants to transition into Data Science & AI
shinyfe74/taipy
Turns Data and AI algorithms into production-ready web applications in no time.
shinyfe74/CodSoft
This was a simple virtual internship where i mainly created machine learning models to perform tasks like Classification & Prediction
shinyfe74/100-Days-of-DataScience
Greetings! ๐ I'm Loga Aswin, diving into a 100-day data science immersion from Python fundamentals to real-world applications. This space will be a live documentation of my journey, where code meets curiosity. Let's connect, learn, and code together. Click โญ on GitHub to stay tuned for updates on my work!
shinyfe74/Step_by_Step_to_Learn_Data_Science
shinyfe74/data_analysis_course
๋น ๋ฐ์ดํฐ ๋ถ์ ์ฝ์ค ๊ฐ์ ์๋ฃ
shinyfe74/modality_selection
For test user's modality selection in multimodal system.
shinyfe74/retail-project
์๊ฑฐ๋ ๋ฐ์ดํฐ๋ฅผ ์ด์ฉํ ์ฝํธํธ, ํผ๋, RFM ๊ณ ๊ฐ ์ธ๋ถํ ๋ถ์
shinyfe74/Titanic_Prediction
Learn machine learning from Titanic disaster
shinyfe74/foundations
Source Code for Solomon's Link
shinyfe74/Image_harmony
calculate image color harmony by color hue degree
shinyfe74/DA_DS_Book001
DA_DS_Book001
shinyfe74/python_data_basic
'ํ์ด์ฌ์ผ๋ก ์์ํ๋ ๋ฐ์ดํฐ ๋ถ์' ์ฝ๋ ์ ์ฅ์
shinyfe74/Data-Analyst-Roadmap
Data-Analyst-Roadmap for Professionals. This roadmap contains 8 Chapters that can be completed in 8 weeks, whether you are a fresher in the field or an experienced professional who wants to transition into Data Analysis.
shinyfe74/noviceml
๋์ ๋จธ์ ๋ฌ๋ยท๋ฅ๋ฌ๋์ ํ์ํ ๊ธฐ์ด ์ํ with ํ์ด์ฌ์ ์์ ์ฝ๋์ ๊ทธ๋ํ ๊ทธ๋ฆฌ๋ ์ฝ๋ ๋ฐ ์น์ฑ ์ ์ฅ์
shinyfe74/google-data-analytics
google data analytics professional certificate
shinyfe74/drag_n_drop_fitts_law
shinyfe74/grid_fitts_law
shinyfe74/Python-For-Data-Professionals
This course is designed to get a good grip on python programming, logic building, solving algorithm-based questions, data structures, understanding of data analytics, working with pandas, professional practices, and API building.
shinyfe74/Python-Machine-Learning-By-Example-Third-Edition
Python Machine Learning By Example Third Edition, published by Packt
shinyfe74/2022.AI
2022-2ํ๊ธฐ ์ง๋ฅ๊ธฐ์ ๊ณตํ๋ถ ์ธ๊ณต์ง๋ฅ ์์
shinyfe74/2021.ArtificialIntelligence
2021-2ํ๊ธฐ ์ง๋ฅ๊ธฐ์ ๊ณตํ๋ถ ์ธ๊ณต์ง๋ฅ์์
shinyfe74/Image_diversity
calculate image color diversity by fractal dimension using box-counting method
shinyfe74/foundations-for-analytics-with-python
shinyfe74/Ratio_Template_Matching
This code is for template matching when the template image has different size from original image.