bharddwaj

import tensorflow as tf
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

msft = pd.read_csv("MSFT.csv")

print(msft.shape)
msft_returns = []
for i in range(1,1259):

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/*******************************************************************************
* Name        : waterJugPuzzle.cpp
* Author      : Bharddwaj Vemulapalli
* Date        :  March 13, 2020
* Description : Solves the water jug puzzle.
* Pledge      : I pledge my honor that I have abided by the Stevens Honor System.
******************************************************************************/
#include <iostream>
#include <sstream>
#include <vector>

bharddwaj

//
//  main.cpp
//  GameAndWatch
//
//  Created by Bharddwaj Vemulapalli on 2/7/20.
//  Copyright © 2020 Bharddwaj Vemulapalli. All rights reserved.
//

#include <iostream>
#include <random>

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import random

def SingleDimensionWalk(x,count):
    '''
    Write a program to simulate a random walk in one dimension starting at 0. 
    Have your program print out the lengths of the times between returns to the starting point (returns to 0).
    '''
    if random.randint(0,1):
        x+=1
    else:

bharddwaj

package homework;
import java.util.Random;
import java.util.Stack;
/**
 * @param <E>
 */
//Bharddwaj Vemulapalli
//CS284
//I pledge my honor that I have abided by the Stevens Honor System.
public class treap<E extends Comparable<E>>{

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def LinearRegression(x,y,round_digits):
    ''' 
        x: feature vector (Preferably Numpy Array)
        y: dependent vector (Preferably Numpy Array)
        round_digits: number of digits you want to round the final equation to
        This function returns the Ordinary Least Squares Regression model.
    '''
    c = np.ones((len(x[0]),))
    A = []
    A.append(c)

bharddwaj

import pandas as pd
import numpy as np
import csv
import seaborn as sns
import matplotlib.pyplot as plt
import math
from collections import OrderedDict
data = pd.read_csv("CL_June_2019.csv")
print(type(data))

bharddwaj

import pandas as pd
import numpy as np
import csv
import seaborn as sns
import matplotlib.pyplot as plt
import math

data = pd.read_csv("CL_June_2019.csv")
print(type(data))
#new_data = data[59528000:59800000]

bharddwaj

import pandas as pd
import numpy as np
import csv
import seaborn as sns
import matplotlib.pyplot as plt
import math

data = pd.read_csv("CL_June_2019.csv")

#new_data = data[59528000:59800000]

bharddwaj

import pandas as pd
import numpy as np
import csv
import seaborn as sns
import matplotlib.pyplot as plt
import math

data = pd.read_csv("CL_June_2019.csv")
print(type(data))
#new_data = data[59528000:59800000]