Mahedi-61

1. DP (canSum) Given a target sum and an array of positive integers,
return true if the target sum can be constructed by summing any combination of elements from the array.
You may use an element of the array as many times as needed.

#Solution
def canSum(nums, target, memo={}):
    if target in memo: return memo[target]
    if target == 0: return True
    elif target < 0: return False 
    

Mahedi-61

1. FourSum:
You are given an integer array nums of size n, return an array of all the unique quadruplets 
[nums[a], nums[b], nums[c], nums[d]] such that:

0 <= a, b, c, d < n
a, b, c, and d are distinct.
nums[a] + nums[b] + nums[c] + nums[d] == target
You may return the answer in any order. Note: [1,0,3,2] and [3,0,1,2] are considered as same quadruplets.
Example 1:
Input: nums = [3,2,3,-3,1,0], target = 3

Mahedi-61

##### 1. List Rotate
You are given a list of n integers and a non-negative integer k.

Your task is to write a function called rotate that takes the list of integers and an integer k as input and rotates the 
list to the right by k steps. The function should modify the input list in-place, and you should not return anything.
Constraints:
    Each element of the input list is an integer.
    The integer k is non-negative.

Function signature: def rotate(nums, k):

Mahedi-61

def bubble_sort(my_list):
    for i in range(len(my_list)-1, 0, -1): #steps
        for j in range(0, i):
            
            if my_list[j] > my_list[j+1]:
                temp = my_list[j]
                my_list[j] = my_list[j+1]
                my_list[j+1] = temp 
        
    return my_list

Mahedi-61

import torch
import torch.optim as optim
import numpy as np 
from matplotlib import pyplot as plt 
from tabnanny import check
from sklearn.metrics import confusion_matrix
import seaborn as sns 
from torch import nn 
import torch.nn.init as init
from torchvision import transforms, datasets

Mahedi-61

"""
modified from several gist of https://gist.github.com/tarlanahad
For Homework Assingment 12 (CpE 520)
"""

import numpy as np
import torchvision
from matplotlib import pyplot as plt 
from sklearn.metrics import confusion_matrix
import seaborn as sns 

Mahedi-61

"""
Author: Md Mahedi Hasan 
For Homework Assingment 12 (CpE 520)
"""

import numpy as np
import os
import matplotlib.pyplot as plt
from torch.utils.data import DataLoader
from torchvision import transforms

Mahedi-61

"""
Script to implement simple self organizing map 
@author: Riley Smith
Created: 1-27-21
"""
"""
@modified: Md Mahedi Hasan (11/28/2021)
For Homework Assingment 11 (CpE 520
"""

Mahedi-61

"""
Course: Applications of NN (CpE - 520)
Homework Assignment 9
"""

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

Mahedi-61

# solving parity-3 problems using numpy only

from os import error
import numpy as np
import math 
np.random.seed(1)


def relu(x):
    return np.maximum(0, x)