JyotinderSingh

class Solution {
public:
    int numTrees(int n) {
        vector<int> G(n + 1, 0);
        G[0] = 1, G[1] = 1;
        
        // Iterating for different values of N, in Bottom Up Approach
        for(int i = 0; i <= n; ++i) {
            
            // Looking at each case with all nodes as roots

JyotinderSingh

// https://leetcode.com/problems/3sum/
// Explanation:
// https://youtu.be/6WsddbKA_vg
class Solution {
public:
    vector<vector<int>> threeSum(vector<int>& nums) {
        vector<vector<int>> res;
        if(nums.size() < 3) {
            return res;
        }

JyotinderSingh

class Solution {
public:
    vector<int> twoSum(vector<int>& nums, int target) {
        unordered_map<int, int> mp;
        
        for(int i = 0; i < nums.size(); ++i) {
            int complement = target - nums[i];
            
            if(mp.find(complement) != mp.end()) {
                return {mp[complement], i};

JyotinderSingh

// https://youtu.be/9PC2r6MAw1Q
// https://leetcode.com/problems/dungeon-game/
class Solution
{
public:
    int calculateMinimumHP(vector<vector<int>> &dungeon)
    {
        if (dungeon.size() == 0 || dungeon[0].size() == 0)
            return 1;
        /*

JyotinderSingh

// https://leetcode.com/problems/subarray-sum-equals-k/
class Solution {
public:
    int subarraySum(vector<int> &nums, int k)
{
    unordered_map<int, int> map;
    int count = 0;
    // maintains sum of elements so far
    int curr_sum = 0;

JyotinderSingh

from tensorflow.keras.preprocessing.image import ImageDataGenerator
from tensorflow.keras.optimizers import RMSprop
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import os
import tensorflow as tf
import zipfile

base_dir = '/home/jyotinder/Programming/DeepLearning/dataset/dogs-vs-cats'
train_dir = os.path.join(base_dir, 'train')