Yeaseen

[
    {
    "_id": "5f4011d1fadf274a8862865a",
    "title": "ad labore tempor eiusmod et",
    "description": "Minim enim deserunt id aliquip tempor elit amet culpa voluptate officia pariatur voluptate adipisicing. Enim ex anim enim voluptate minim esse. Dolore dolore ad nostrud sint. Adipisicing ex voluptate veniam in elit pariatur irure pariatur tempor irure ex amet quis. Proident incididunt non qui consequat duis Lorem in labore sunt Lorem adipisicing anim eiusmod. Nisi Lorem nostrud deserunt reprehenderit enim quis eu duis minim enim. Eiusmod anim voluptate dolore exercitation qui cupidatat nostrud pariatur.\r\nId laborum velit Lorem culpa. Ipsum velit laboris est laborum minim exercitation. Pariatur esse occaecat occaecat duis eiusmod reprehenderit labore commodo officia ea. Labore ut labore ad in. Elit consequat do fugiat sit. Ex eu dolor nulla quis ipsum. Adipisicing velit duis excepteur fugiat.\r\n",
    "picture": "https://placehold.it/500x500",
    "price": 37,
    "stock": 7
  },
  {

Yeaseen

import React, { useState, useEffect } from 'react'
import { useHistory } from 'react-router-dom'


import Swal from "sweetalert2";
const CreatePost = () => {

    const history = useHistory()
    const [title, setTitle] = useState("")
    const [body, setBody] = useState("")

Yeaseen

#include <iostream>
#include <cmath>
using namespace std;

 struct Data{

     double key;
     double x;
     double y;

Yeaseen

!apt-get install -y -qq software-properties-common module-init-tools
!add-apt-repository -y ppa:alessandro-strada/ppa 2>&1 > /dev/null
!apt-get update -qq 2>&1 > /dev/null
!apt-get -y install -qq google-drive-ocamlfuse fuse




from google.colab import auth
from oauth2client.client import GoogleCredentials

Yeaseen

homogeneous_point intersect(homogeneous_point p3,homogeneous_point p2, double z){
    homogeneous_point ans;
    ans.w=1;
    ans.z=z;
    ans.x=p2.x + ((p3.x-p2.x)/(p3.z-p2.z))*(z-p2.z);
    ans.y=p2.y + ((p3.y-p2.y)/(p3.z-p2.z))*(z-p2.z);
    //ans.print();
    return ans;
}

Yeaseen

#include <iostream>
#include <fstream>
#include <cassert>
#include <iomanip>
#include <cmath>
#include <stack>
#include <queue>
#include "bitmap_image.hpp"
using namespace std;

Yeaseen

M = np.mean(train.T, axis=1)
C= M - train
V=np.cov(C.T)

eigenValues, eigenVectors =eig(V)
k=2
idx = eigenValues.argsort()[-k:][::-1]
eigenValues = eigenValues[idx]
eigenVectors = eigenVectors[:,idx]

Yeaseen

for i in range(train.shape[0]):
        v=[]
        y=[]
        inputNeuron = [train[i]]
        v.append(inputNeuron)
        y.append(inputNeuron)
        
        for r in range(len(layerNeurons) -1):
            w=weight[r]
            matout=np.matmul(inputNeuron,w)

Yeaseen

def AdaBoost(funcDcsn, sampleFrames, attList, \
             parentFrames,strtdepth, maxdepth,funcClassify,rootClass, K):
    Y=sampleFrames.iloc[:,-1].values.tolist().copy()
    #print(Y)
    N=len(sampleFrames)
    w= [1/N] * N
    h= []
    z= []
    #print(w)

Yeaseen

     //forward differencing method for rendering curve points
     int t=20;
     double space=0.05;
     double fx,fy,f1x,f2x,f3x,f1y,f2y,f3y;
     fx=ansMat[3][0];
     fy=ansMat[3][1];

     f1x= ansMat[0][0]*pow(space,3)+ ansMat[1][0]*pow(space,2)+ansMat[2][0]*space;
     f2x=6*ansMat[0][0]*pow(space,3)+ 2*ansMat[1][0]*pow(space,2);