contropist

class LinearRegression {
    w: Mat;
    constructor() { }

    //x: M-by-N matrix. M data with N dimensions. Each row is an N-dim vector
    //y: M-by-1 matrix
    fit(x_: Mat, y_: Mat) : LinearRegression{
        let y = y_;        
        if (y_.rows != 1 && y_.cols == 1) {y = y_.T();}  //check the dimension of y
        var x = x_.resize(x_.rows, x_.cols + 1, 1);   //expan x_ with one more column with 1

contropist

-- 只扫原生WS,不要太恐慌.

local stdnse = require "stdnse"
local http = require "http"

categories = { "default", "discovery", "safe" }

portrule = function(host, port)
	return true
end

contropist

import requests
import json
import base64
import sqlite3
import zlib
import time
from datetime import datetime
from gql import gql, Client
from gql.transport.requests import RequestsHTTPTransport

contropist

Setup:

1. Add this code to your ~/.bash_aliases file.

function gdrive_download () {
  CONFIRM=$(wget --quiet --save-cookies /tmp/cookies.txt --keep-session-cookies --no-check-certificate "https://docs.google.com/uc?export=download&id=$1" -O- | sed -rn 's/.*confirm=([0-9A-Za-z_]+).*/\1\n/p')
  wget --load-cookies /tmp/cookies.txt "https://docs.google.com/uc?export=download&confirm=$CONFIRM&id=$1" -O $2
  rm -rf /tmp/cookies.txt
}

contropist

#!/bin/bash

set -e

# Put
# 1. CUDA installation script (cuda_*.run, see https://developer.nvidia.com/cuda-downloads)
# 2. cuDNN archive (cudnn-*.tgz, see https://developer.nvidia.com/rdp/cudnn-download)
# 3. Intel MKL archive (l_mkl_*.tgz, see https://software.intel.com/en-us/intel-mkl)
# under $HOME
# Also set INTEL_MKL_SN to Intel MKL's serial number (XXXX-XXXXXXXX)

contropist

git config --global https.proxy http://127.0.0.1:1080

git config --global https.proxy https://127.0.0.1:1080

git config --global --unset http.proxy

git config --global --unset https.proxy


npm config delete proxy

contropist

—– BEGIN LICENSE —–
Anthony Sansone
Single User License
EA7E-878563
28B9A648 42B99D8A F2E3E9E0 16DE076E
E218B3DC F3606379 C33C1526 E8B58964
B2CB3F63 BDF901BE D31424D2 082891B5
F7058694 55FA46D8 EFC11878 0868F093
B17CAFE7 63A78881 86B78E38 0F146238
BAE22DBB D4EC71A1 0EC2E701 C7F9C648

contropist

一直都喜欢用markdown记录东西，即使平时用的某云笔记并不支持markdown，也还是习惯保持markdown格式的记录。最近Medium比较火，就试着把之前写好的一篇文章发到Medium上去，结果Medium并不支持Markdown，可是在Medium上写作的Geek们自然有办法：

• How to import Markdown into Medium

就是在这里看到了Github的Gist原来可以这么玩，忽然好奇Gist是不是还有其他好玩的玩儿法。一发不可收拾，果然找到了各种花样玩儿法：

• What You Can Do With Gists on Github?

总得来说还是对Gist写东西比较感兴趣，有版本控制，能够设置成别人可见或不可见，还支持协作。Gist写好之后可以通过roughdraft.io发布出来，读起来很方便。

contropist

ACM大量习题题库 

ACM大量习题题库 
现在网上有许多题库，大多是可以在线评测，所以叫做Online Judge。除了USACO是为IOI准备外，其余几乎全部是大学的ACM竞赛题库。

USACO

http://ace.delos.com/usacogate

美国著名在线题库，专门为信息学竞赛选手准备

contropist

#!/usr/bin/env python

"""
=====================================
PEP 20 (The Zen of Python) by example
=====================================

Usage: %prog

:Author: Hunter Blanks, hblanks@artifex.org / hblanks@monetate.com