๐๐ฆ ๐๐น๐ด๐ผ ๐ป ๐ ใ๐๐ผ๐บ๐ฝ๐ฒ๐๐ถ๐๐ถ๐๐ฒ ๐ฃ๐ฟ๐ผ๐ด๐ฟ๐ฎ๐บ๐บ๐ถ๐ป๐ดใ
class UserMainCode(object): @classmethod def theLastChocolate(cls, input1, input2): dp = [[0] * (input1 + 1) for _ in range(input1 + 1)] dp[1][1] = 1 for i in range(2, input1 + 1): for j in range(1, i +โฆ
int gcd(int a, int b) {
while (b != 0) {
int t = b;
b = a % b;
a = t;
}
return a;
}
int calculatesun(int input1, int input2[]) {
// Read only region end
int N = input1;
int max_so_far = input2[0];
for (int i = 0; i < N; ++i) {
max_so_far = std::max(max_so_far, input2[i]);
input2[i] = gcd(input2[i], max_so_far);
}
std::sort(input2, input2 + N);
int sum = 0;
for (int i = 0; i < N / 2; ++i) {
sum += gcd(input2[i], input2[N - 1 - i]);
}
return sum;
}
Sum in Array โ
Amazon ML
while (b != 0) {
int t = b;
b = a % b;
a = t;
}
return a;
}
int calculatesun(int input1, int input2[]) {
// Read only region end
int N = input1;
int max_so_far = input2[0];
for (int i = 0; i < N; ++i) {
max_so_far = std::max(max_so_far, input2[i]);
input2[i] = gcd(input2[i], max_so_far);
}
std::sort(input2, input2 + N);
int sum = 0;
for (int i = 0; i < N / 2; ++i) {
sum += gcd(input2[i], input2[N - 1 - i]);
}
return sum;
}
Sum in Array โ
Amazon ML
Random forest Reg
0.0923
K Nearest Neighbours algorithm. By identifying the similarity in physical features of each herb, it can be classified as a given species.
0.0032, computer = "yes"
K-Means Clustering
import pandas as pd
file = pd.read_csv('salary.csv')
q = [0,.25,.50,.75,1]
label = ['0 to 25', '25 to 50', '50 to 75', '75 to 1']
file['Age_q'] = pd.qcut(file['Age'], q = q, labels = label)
Factor of 4
c1 = (data['Grade'] == 'A') & (data['Marks'] > 60)
c2 = (data['Grade'] == 'B') & (data['Marks'] > 70)
c3 = (data['Grade'] == 'C') & (data['Marks'] > 80)
c = pd.Series(np.select([c1,c2,c3], ['Yes','Yes','Yes'], default='No'), index=data.index)
data['Admission'] = data['Admission'].fillna(c)\
From options (0.371,0.971,0.241.0) => correct => 0 โ
Question=> (Indian,student, male) => answer 1.5 โ
Linear regression question =>high bais, low variance,underfitting of data
Amazon ML MCQ โ
0.0923
K Nearest Neighbours algorithm. By identifying the similarity in physical features of each herb, it can be classified as a given species.
0.0032, computer = "yes"
K-Means Clustering
import pandas as pd
file = pd.read_csv('salary.csv')
q = [0,.25,.50,.75,1]
label = ['0 to 25', '25 to 50', '50 to 75', '75 to 1']
file['Age_q'] = pd.qcut(file['Age'], q = q, labels = label)
Factor of 4
c1 = (data['Grade'] == 'A') & (data['Marks'] > 60)
c2 = (data['Grade'] == 'B') & (data['Marks'] > 70)
c3 = (data['Grade'] == 'C') & (data['Marks'] > 80)
c = pd.Series(np.select([c1,c2,c3], ['Yes','Yes','Yes'], default='No'), index=data.index)
data['Admission'] = data['Admission'].fillna(c)\
From options (0.371,0.971,0.241.0) => correct => 0 โ
Question=> (Indian,student, male) => answer 1.5 โ
Linear regression question =>high bais, low variance,underfitting of data
Amazon ML MCQ โ
def min_key_presses(input1):
S=input1
n = len(S)
i = 0
key_presses = 0
while i < n:
if S[i] == '0':
zero_count = 0
while i < n and S[i] == '0':
zero_count += 1
i += 1
key_presses += zero_count // 2
if zero_count % 2 == 1:
key_presses += 1
else:
while i < n and S[i] != '0':
key_presses += 1
i += 1
return key_presses
Amazon MLโ
S=input1
n = len(S)
i = 0
key_presses = 0
while i < n:
if S[i] == '0':
zero_count = 0
while i < n and S[i] == '0':
zero_count += 1
i += 1
key_presses += zero_count // 2
if zero_count % 2 == 1:
key_presses += 1
else:
while i < n and S[i] != '0':
key_presses += 1
i += 1
return key_presses
Amazon MLโ
Matrix value of x 3
Alphabet count 9:45
F'(x) 1/1+x^4 A
James Simon 1/20
John peter tom 1/4
Equal no of chocolates 7
Exams 86
Students weights 60.2
G(3) 13
Perfect sq 1/3
P -1
Restaurant tables 10
3.45 bits
it learns based on unlabbled data
only D
b and d
Alphabet count 9:45
F'(x) 1/1+x^4 A
James Simon 1/20
John peter tom 1/4
Equal no of chocolates 7
Exams 86
Students weights 60.2
G(3) 13
Perfect sq 1/3
P -1
Restaurant tables 10
3.45 bits
it learns based on unlabbled data
only D
b and d
t1 t2 relation t1>t2
Trigrams c
Age income student comp 1.0
Ek c1 = (data['Grade'] == 'A') & (data['Marks'] > 60)
c2 = (data['Grade'] == 'B') & (data['Marks'] > 70)
c3 = (data['Grade'] == 'C') & (data['Marks'] > 80)
c = pd.Series(np.select([c1, c2, c3], ['Yes', 'Yes', 'Yes'], default='No'), index=data.index)
data['Admission'] = data['Admission'].fillna(c)
Reinforcement learing scenario all A, B, C, D
Yactual ypredicted iska B
Nouns and parts C
Perceptron model 0
Amazon MLโ
Trigrams c
Age income student comp 1.0
Ek c1 = (data['Grade'] == 'A') & (data['Marks'] > 60)
c2 = (data['Grade'] == 'B') & (data['Marks'] > 70)
c3 = (data['Grade'] == 'C') & (data['Marks'] > 80)
c = pd.Series(np.select([c1, c2, c3], ['Yes', 'Yes', 'Yes'], default='No'), index=data.index)
data['Admission'] = data['Admission'].fillna(c)
Reinforcement learing scenario all A, B, C, D
Yactual ypredicted iska B
Nouns and parts C
Perceptron model 0
Amazon MLโ
int solve(int idx, int n, int countZero, vector<vector<int>>& dp) {
int mod=1e4+7;
if (idx >= n) {
if (countZero >= 2)
return 1;
return 0;
}
if (dp[idx][countZero] != -1)
return dp[idx][countZero];
int count = 0;
for (int i = 0; i <= 9; ++i) {
if (idx == 0 && i == 0)
continue;
if (i == 0)
count = (count + solve(idx + 1, n, countZero + 1, dp)) % mod;
else
count = (count + solve(idx + 1, n, countZero, dp)) % mod;
}
return dp[idx][countZero] = count;
}
int bounty(int input1) {
vector<vector<int>> dp(input1 + 1, vector<int>(input1 + 1, -1));
if (input1 < 2)
return 0;
if (input1 == 2)
return 1;
return solve(0, input1, 0, dp);
}
Bounty
Amazon MLโ
int mod=1e4+7;
if (idx >= n) {
if (countZero >= 2)
return 1;
return 0;
}
if (dp[idx][countZero] != -1)
return dp[idx][countZero];
int count = 0;
for (int i = 0; i <= 9; ++i) {
if (idx == 0 && i == 0)
continue;
if (i == 0)
count = (count + solve(idx + 1, n, countZero + 1, dp)) % mod;
else
count = (count + solve(idx + 1, n, countZero, dp)) % mod;
}
return dp[idx][countZero] = count;
}
int bounty(int input1) {
vector<vector<int>> dp(input1 + 1, vector<int>(input1 + 1, -1));
if (input1 < 2)
return 0;
if (input1 == 2)
return 1;
return solve(0, input1, 0, dp);
}
Bounty
Amazon MLโ
John sam 0.88
8 red balls 0.35
Differential b
Alphabet mean 9.45
2 digit number 12
r nonzero k=1
Mean median mode range A
max diff 162
G(3) =13
AA' x=2
profit margin 0.1667
Red 2nd ball black 1st ball 8/13
Apti Answers
Amazon MLโ
8 red balls 0.35
Differential b
Alphabet mean 9.45
2 digit number 12
r nonzero k=1
Mean median mode range A
max diff 162
G(3) =13
AA' x=2
profit margin 0.1667
Red 2nd ball black 1st ball 8/13
Apti Answers
Amazon MLโ
class Compute:
@classmethod
def compute(cls, input1, input2):
n = input1
arr = input2
result = []
for i in range(n):
m = 0
k = n - 2
left = i - 1
right = i + 1
if i == 0:
for i in range(1, k + 1):
m += abs(arr[0] - arr[i])
result.append(m)
else:
while left >= 0 and right < n:
lside = abs(arr[left] - arr[i])
rside = abs(arr[right] - arr[i])
if lside < rside:
m += lside
left -= 1
k -= 1
if k == 0:
break
else:
m += rside
right += 1
k -= 1
if (k == 0):
break
while left >= 0 and k > 0:
m += abs(arr[left] - arr[i])
left -= 1
k -= 1
while right < n and k > 0:
m += abs(arr[right] - arr[i])
k -= 1
right += 1
result.append(m)
return result
Nearest house โ
@classmethod
def compute(cls, input1, input2):
n = input1
arr = input2
result = []
for i in range(n):
m = 0
k = n - 2
left = i - 1
right = i + 1
if i == 0:
for i in range(1, k + 1):
m += abs(arr[0] - arr[i])
result.append(m)
else:
while left >= 0 and right < n:
lside = abs(arr[left] - arr[i])
rside = abs(arr[right] - arr[i])
if lside < rside:
m += lside
left -= 1
k -= 1
if k == 0:
break
else:
m += rside
right += 1
k -= 1
if (k == 0):
break
while left >= 0 and k > 0:
m += abs(arr[left] - arr[i])
left -= 1
k -= 1
while right < n and k > 0:
m += abs(arr[right] - arr[i])
k -= 1
right += 1
result.append(m)
return result
Nearest house โ
Forwarded from OffCampus Jobs | OnCampus Jobs | Daily Jobs Updates | Lastest Jobs | All Jobs | CSE Jobs | Fresher Jobs โฅ (Dushyant)
I can't believe how far we've come together on this journey. A big thank you to each and every one of you for supporting me, leaving kind comments, and pushing me to keep creatingโคโ๐ป
def op(players, trainers):
players.sort()
trainers.sort()
count = 0
startT = 0
startP = 0
while startT < len(trainers) and startP < len(players):
if players[startP] >= trainers[startT]:
startP+=1
startT+=1
count+=1
else:
startP+=1
return count
Red Bus โ
players.sort()
trainers.sort()
count = 0
startT = 0
startP = 0
while startT < len(trainers) and startP < len(players):
if players[startP] >= trainers[startT]:
startP+=1
startT+=1
count+=1
else:
startP+=1
return count
Red Bus โ
Forwarded from OffCampus Jobs | OnCampus Jobs | Daily Jobs Updates | Lastest Jobs | All Jobs | CSE Jobs | Fresher Jobs โฅ (Dushyant)
Rupeek is hiring for Android Engineer (2021, 2022 and 2023 grads)
JD: https://docs.google.com/document/u/0/d/1RYlGWEH31KPt5-YZ4G5PSMgrmaMywv-KQpQbPz1mBA4/mobilebasic
Apply Link: https://docs.google.com/forms/d/e/1FAIpQLSfz7XamMLri24X64d-B58m2H70YZl9aItL_o3Hv4N5r-PnVNg/viewform?usp=send_form
JD: https://docs.google.com/document/u/0/d/1RYlGWEH31KPt5-YZ4G5PSMgrmaMywv-KQpQbPz1mBA4/mobilebasic
Apply Link: https://docs.google.com/forms/d/e/1FAIpQLSfz7XamMLri24X64d-B58m2H70YZl9aItL_o3Hv4N5r-PnVNg/viewform?usp=send_form
Forwarded from OffCampus Jobs | OnCampus Jobs | Daily Jobs Updates | Lastest Jobs | All Jobs | CSE Jobs | Fresher Jobs โฅ (Dushyant)
setlmint.com is hiring Full Stack Engineer
For 2024 grads
Check out this job at setlmint.com: https://www.linkedin.com/jobs/view/3957631749
For 2024 grads
Check out this job at setlmint.com: https://www.linkedin.com/jobs/view/3957631749
Linkedin
setlmint.com hiring Full Stack Engineer in Mumbai, Maharashtra, India | LinkedIn
Posted 7:03:34 AM. Full Stack developer role - high growth and high energy environment - FRESHERS ONLYFreshers only***โฆSee this and similar jobs on LinkedIn.
#include<bits/stdc++.h>
using namespace std;
#define int long long
signed main()
{
int t;
cin>>t;
while(t--)
{
int m;
cin>>m;
int l;
cin>>l;
int a[l];
for(int i=0;i<l;i++) cin>>a[i];
int r;
cin>>r;
int b[r];
for(int i=0;i<r;i++) cin>>b[i];
int i=0;
int j=0;int price=0;int cnt=0;
while(i<l and j<r and price<=m)
{
if(a[i]>=a[j]) {price+=a[j];cnt++;j++;}
else {price+=a[i];cnt++;i++;}
}
cout<<cnt<<endl;
}
}
Sheldon And Penny โ