yusong-shen

import java.io.*;
import java.util.*;

public class BathroomStalls {

	public BathroomStalls() {
		// TODO Auto-generated constructor stub
	}
	
	// O(k * n * logn)

yusong-shen

var map = {}
data_list.forEach( item => {
	item['code_tags'].forEach( tag => {
		if (tag in map) {
			map[tag] += 1;
		} else {
			map[tag] = 1;
		}
	})

yusong-shen

var table = document.getElementsByTagName('tbody');

var q_table = table[0];

// DOM Node List
var all_data = q_table.getElementsByTagName('tr');

var data_list = []

yusong-shen

原文地址：http://in.sdo.com/?p=1707
收集和整理了目前互联网上能找到的开源推荐系统，并附上了个人的一些简单点评（未必全面准确），这个列表是目前为止比较全面的了，希望对大家了解掌握推荐系统有帮助（文/陈运文）
SVDFeature
由上海交大的同学开发，采用C++语言，代码质量很高。去年我们参加KDD竞赛时用过，很好很方便，而且出自咱们国人之手，所以置顶推荐！
项目地址：
http://svdfeature.apexlab.org/wiki/Main_Page
SVDFeature包含一个很灵活的Matrix Factorization推荐框架，能方便的实现SVD、SVD++等方法, 是单模型推荐算法中精度最高的一种。SVDFeature代码精炼，可以用相对较少的内存实现较大规模的单机版矩阵分解运算。
另外含有Logistic regression的model，可以很方便的用来进行ensemble运算

yusong-shen

"""
Implementations of:

    Probabilistic Matrix Factorization (PMF) [1],
    Bayesian PMF (BPMF) [2],
    Modified BPFM (mBPMF)

using `pymc3`. mBPMF is, to my knowledge, my own creation. It is an attempt
to circumvent the limitations of `pymc3` w/regards to the Wishart distribution:

yusong-shen

"""
Code for training RBMs with contrastive divergence. Tries to be as
quick and memory-efficient as possible while utilizing only pure Python
and NumPy.
"""

# Copyright (c) 2009, David Warde-Farley
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without