private

protected

public

public and abstract

O(N)

O(log N)

O(N log N)

O(N!)

A

B

C

D

2^22

2^24

2^16

(2^24)-2

POST

PUT

GET

DELETE

Encrypting website data

Translating domain names to IP addresses

Managing server hardware

Creating website layouts

It ensures that every row in a table has a unique identifier

It specifies a column or set of columns that uniquely identifies a row in another table

It enforces rules for data manipulation in a table

It ensures that the values in a column are not NULL

Length of string: 0

Length of string: null

Exception Caught: NullPointerException

Exception Caught: null

ping

traceroute

netstat

nslookup

2 3 4 5 6 7 8 9 10

1 2 3 4 5 6 7 8 9 10

1 2 3 4 5 6 7 8 9

2 3 4 5 6 7 8 9

ridge solves the problem of overfitting while lasso solves both the problem of overfitting and feature selection

ridge solves the problem of underfitting while lasso solves the problem of overfitting

ridge solves the problem of overfitting and feature selection while lasso solves the problem of overfitting

ridge solves the problem of both overfitting and underfitting while lasso solves the problem of overfitting only

it eliminates nodes from the hidden layer

it helps in determining which activation function is needed such as : ReLU , sigmoid , linear etc ...

it is used for determining the mathematical formula for neural networks

it helps to reduce the loss function until it reaches the global minima

High bias , High variance

low bias , high variance

high bias , low variance

low bias , low variance

f(x) = max (1,x)

f(x) = max(0,x)

f(x) = min(0,x)

f(x) = max (0.5, x)