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frankfan007's Projects

img2latex-mathpix

An image to LaTeX tool by Mathpix OCR API

imhex

A Hex Editor for Reverse Engineers, Programmers and people that value their eye sight when working at 3 AM.

imm-sensors-network

Project for the course "Distributed Systems for measurement and automation".

ims

📚 Introduction to Modern Statistics - A college-level open-source textbook with a modern approach highlighting multivariable relationships and simulation-based inference.

influential-cs-books

Most influential books on Computer Science/programming

info_geometry

Code to accompany the paper "The Information Geometry of Unsupervised Reinforcement Learning"

interactive-gp-visualization

Interactive visualization of Gaussian processes

interpretable-ml-article

Code examples for my Interpretable Machine Learning Blog Series

interpretable-ml-book

Book about interpretable machine learning

interpretablemlbook

《可解释的机器学习--黑盒模型可解释性理解指南》，该书为《Interpretable Machine Learning》中文版

iptv

Collection of 8000+ publicly available IPTV channels from all over the world

isofpd

community detection based on density-based clustering

isonet

Repository for "Deep Isometric Learning for Visual Recognition"

javascript

A repository for All algorithms implemented in Javascript (for educational purposes only)

javascript-algorithms

📝 Algorithms and data structures implemented in JavaScript with explanations and links to further readings

jfe

:exclamation: This is a read-only mirror of the CRAN R package repository. JFE — Tools and GUI for Analyzing Data of Just Finance and Econometrics

jpdaf_tracking

A tracker based on joint probabilistic data association filtering.

jupyter-book

Build interactive, publication-quality documents from Jupyter Notebooks

justwrite

增强版的Typora Plus，跨平台Markdown编辑器，微信公众号文章排版，自带新浪微博免费图床，Markdown个人简历，一键发布文章到博客园、CSDN、SegmentFault、掘金、开源**等平台。

kdd20-tutorial

Tutorial on Automated Machine Learning at KDD 2020

kdd2019_k-multiple-means

Implementation for the paper "K-Multiple-Means: A Multiple-Means Clustering Method with Specified K Clusters,", which has been accepted by KDD'2019 as an ORAL paper, in the Research Track.

We develop the clustering approach by fast-search-and-find of density peaks which use the kernel function for mapping the input sample objects to the high dimensional feature space and amplifying the original sample objects’ characteristics, thereby researching the local density of the object attribute based on similarity measure. In order to identify our method’s effectiveness, we compare our method to other popular clustering algorithms. From the result analysis, we could conclude that our method have a better result.

key-book

《机器学习理论导引》（宝箱书）的证明、案例、概念补充与参考文献讲解。在线阅读地址：https://datawhalechina.github.io/key-book/

frankfan007 Goto Github PK

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