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algorithm's Introduction

注：

《机器学习数学基础》勘误和修订

Github 上的 Markdown 文档：https://github.com/qiwsir/Math4ML_book/blob/main/corrigendum.md
百度网盘下载 PDF 文档：链接: https://pan.baidu.com/s/1OOimHFaTJ-CxmeCvnADFPQ 提取码: d3a5

《机器学习数学基础》拓展资料：https://github.com/qiwsir/Math4ML_book/blob/main/SUMMARY.md

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algorithm's Issues

操作二维整数数组里分数没有区分课程

目前的算法分数没有区分课程，那么给定课程的信息对比算法变成了冗余的。
如果要区分课程的话，用nameturple会不会更好一些？

哪错了？齐老板

二分查找算法实现一文作者不小心，有误

原谅：

也可以不用递归方法，而采用循环，如下：

def binarySearch(lst, value,low,high):          #low,high是lst的查找范围
    if high < low:
        return -1
    mid = (low + high)/2
    if lst[mid] > value:
        return binarySearch(lst, value, low, mid-1)
    elif lst[mid] < value:
        return binarySearch(lst, value, mid+1, high)
    else:
        return mid

最后应该是
return lst[mid]

另外当 high< low 时返回-1 ，对此不解。应该返回None

method 2 in quick_sort.md may have a syntax error

the statement is awesome but there are bugs in the code of method 2

def qsort(L):
    return (qsort([y for y in L[1:] if y <  L[0]]) +
                  L[:1] + 
                  [y for y in L[1:] if y == L[0] + qsort([y for y in L[1:] if y > L[0]]) ) \
                  if len(L) > 1 else L

'[' does not appear in pairs.

maybe you need a ']' after if y == L[0] in line 4.

查找字符串中出现最多的字符和个数：Ruby

str.split('').uniq.map {|x| [x, str.count(x)]}.sort{|a,b| b[1]<=>a[1]}[0]

str = "sdsdsddssssssdd"
str.split('').uniq.map {|x| [x, str.count(x)]}.sort{|a,b| b[1]<=>a[1]}[0]
# => ["s", 9]

fib数列

def fib1(n):
if n == 0:
return 0
elif n == 1:
return 1
else:
return fib1(n-1) + fib1(n-2)

memo = {0:0, 1:1}
def fib2(n):
if not n in memo:
memo[n] = fib2(n-1)+fib2(n-2)
return memo[n]

第二种方法似乎不会在计算上有什么优势，求大于1的fib数列都需要全部计算一次。

string_to_hump.md 里的python代码似乎可以写得更简单一些

比如这样：

#! /usr/bin/env python

print "Please input a name:"
snake_case = raw_input()
camelCase = []
for ch in snake_case.split("_"):
    camelCase.append(ch.title())
print "".join(camelCase)

Ivo Ricardo

HFBW 2SKL OVXD EZCT JJXF KMTS N5XE YUKE

数值转化

mid = (low + high)/2,建议用int()转换成整型,不然会报错:
mid = int((low + high)/2)

index_search_whoosh.md 中，parse的问题

from whoosh.qparser import QueryParser
with ix.searcher() as searcher:
    query = QueryParser("content",ix.schema).parse("second")
    result = searcher.search(query)
    results[0]

其中parse是否也可以先分词呢

sir?

dijkstra 算法在机器上跑过没？明显有错误啊！对照这里，缩进错误

如果可以，希望大侠多点注释

附：
priorityDictionary

有点意思
整数list，将偶数放到前面，奇数放到后面

>>> def odd_even(l):
...     return [i for i in l if (~i&1)] + [j for j in l if (j&1)]