EssamWisam

EssamWisam

def dfs(graph, start):
    """
    Perform Depth-First Search (DFS) on a graph starting from a given node.
    
    Args:
        graph: Dictionary representing the adjacency list of the graph
        start: Starting node for DFS
        
    Returns:
        Dictionary with discovery and finish times for each node

EssamWisam

#include <stdio.h>
#include <stdlib.h>

// Define a structure for DynamicArray
typedef struct {
    int *data;      // Pointer to the array of elements
    int size;       // Number of elements currently in the array
    int capacity;   // Total capacity (allocated memory) of the array
} DynamicArray;

EssamWisam

EssamWisam

#include <stdio.h>
#include <stdlib.h>
#include <math.h>

#define LOAD_FACTOR_UPPER 1.0
#define LOAD_FACTOR_LOWER 0.25
#define INITIAL_CAPACITY 8

// ------------------- Node & Doubly Linked List -------------------
typedef struct Node {

EssamWisam

#include <iostream>
#include <stdexcept>

// Fixed sizes for each data structure
#define STACK_SIZE 5
#define QUEUE_SIZE 5
#define LIST_SIZE 10

// --------------------------
// Stack Class Implementation

EssamWisam

EssamWisam

import torch
import numpy as np
import matplotlib.pyplot as plt

# Imagine this is loss function 
def polynomial(w):
    return (w**5 - 3*w**4 + 2*w**3 + w**2 - w + 1)/100000

# Imagine this is loss function multiplied by 10000
def scaled_polynomial(w):

EssamWisam

class MinHeap:
    def __init__(self, data=None):
        """
        Initialize a Min Heap.
        :param data: Optional list to build the heap from.
        """
        self.heap = data if data else []
        if data:
            self.build_min_heap()
    

EssamWisam

def fib(n, depth=0):
    indent = "  " * depth  # Indentation for better visualization
    print(f"{indent}fib({n}) called")

    if n == 0:
        print(f"{indent}Returning 0")
        return 0
    if n == 1:
        print(f"{indent}Returning 1")
        return 1