You've probably already done this, or it came with the stock macbook:
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function success = main() | |
a = ["hello"; "unsorted"; "world"; "moobar"] | |
b = cellstr(a) | |
find(ismember(b, 'world')) %returns 3 | |
function i = binsearch(array, val, low, high) | |
%binary search algorithm for numerics, Usage: | |
%myarray = [ 30, 40, 50.15 ]; %already sorted list | |
%binsearch(myarray, 30, 1, 3) %item 30 is in slot 1 | |
if ( high < low ) |
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#!/usr/bin/python3 | |
# coding: utf-8 | |
import requests | |
from bs4 import BeautifulSoup | |
from scrapy import Selector | |
import csv | |
import datetime | |
#pip3 install --user bs4 |
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function! CommaAQueryChtServer() | |
"setting command hight sets a tolerance for that many echos before you get a "press enter to continue" | |
execute "set cmdheight=5" | |
let word_under_cursor = expand("<cword>") | |
"risky negative 1 at end there, if selection is nothing, that's off screen could be an error | |
let visual_mode_selection = getline("'<")[getpos("'<")[2]-1:getpos("'>")[2]-1] | |
if visual_mode_selection != '' |
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""" | |
This is a batched LSTM forward and backward pass | |
""" | |
import numpy as np | |
import code | |
class LSTM: | |
@staticmethod | |
def init(input_size, hidden_size, fancy_forget_bias_init = 3): |
Open AI gym lunar lander Genetic algorithm.
https://gym.openai.com/evaluations/eval_FbKq5MxAS9GlvB7W6ioJkg
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package JavaApplication12; | |
import java.util.ArrayList; | |
public class Main{ | |
public static void main(String[] args) | |
{ | |
ArrayList<Double> arr = new ArrayList<Double>(); |