tomer-ben-david

class Solution {
    public int lengthOfLongestSubstring(String s) {
        int l = 0;
        int result = 0;
        Set<Character> set = new HashSet<>();
        // We start with right pointer from 0, both left and right are at 0!.
        for (int r = 0; r < s.length(); r++) { 
            // As long as we have duplicates move left first. Trick! at first 0,0 no duplicates!
            while (set.contains(s.charAt(r))) { 
                set.remove(s.charAt(l)); // Note we remove what left points to! until we remove all duplicates with left.

tomer-ben-david

_

tomer-ben-david

// ==UserScript==
// @name         Interview Run Code
// @namespace    http://tampermonkey.net/
// @version      0.1
// @description  try to take over the world!
// @author       You
// @include      https://repl.it/*
// @include      http://tomer-test-public.s3-website-us-west-2.amazonaws.com/*
// @grant        none
// @require      http://code.jquery.com/jquery-3.3.1.min.js

tomer-ben-david

brew install libpq
```R
install.packages('RPostgres')
library(RPostgres)
pconn_r <- dbConnect(RPostgres::Postgres(),
               host = host,
               port = port,
               user = user,
               password = password,
               dbname = dbname,

tomer-ben-david

scala

mockito

import org.scalatest.mock.MockitoSugar
import org.mockito.Mockito._

with MockitoSugar

tomer-ben-david

BigDecimal(1.002).setScale(2, BigDecimal.RoundingMode.HALF_UP).doubleValue() // Round double to #.##

| **Spark Term**                                               | **Description**                                              |
| ------------------------------------------------------------ | ------------------------------------------------------------ |
| Spreadsheet                                                  | Think of data as spreadsheet                                 |
| Statistical learning                                         | Output = f(input) # => f(inputVariable) or f(inputVector), or f(independent variables) or Y = F(X) // X1,X2,.. |
| Programming learning                                         | OutputAttributes = Program(InputAttributes) or Program(InputFeatures) or Model = Algorithm(Data) |
| Error                                                        | Y = f(X) + e # => You learn a function!                      |
| Parametric learning                                          | No 

tomer-ben-david

> df <- data.frame(x=c("spam", "spam", "ham"), y=c("some mail", "some other mail", "some third mail"))
> add.string.func <- function(somestr) { paste("prefix-", somestr, "-postfix", sep = "") }
> df[1,]
     x         y
1 spam some mail
> df[,1]
[1] spam spam ham 
Levels: ham spam
> apply(X = df[1,], add.string.func, MARGIN = 1)
     1                         

tomer-ben-david

df <- data.frame(x=c("spam", "spam", "ham"), y=c("some mail", "some other mail", "some third mail"))
names(df) <- c("Label", "Text")
df$Label <- as.factor(df$Label) // Fill by label would not work if not factor.
df$TextLength <- nchar(as.character(df$Text))
View(df)
ggplot(df, aes(x = TextLength, fill = Label)) + theme_bw() +
         geom_histogram(binwidth = 5) +
         labs(y = "Text Count", x = "Length of Text", title = "Distribution of text on labels")

tomer-ben-david

library(RCurl)
library(bitops)
URL = "https://d396qusza40orc.cloudfront.net/getdata%2Fdata%2Fss06hid.csv"
x = getURL(URL)
out = read.csv(textConnection(x))
head(out[1:6])

tomer-ben-david

mylog <- readLines("./reputation") # => R read load text file