Tip 1 : Participate in live contests on online coding websites as much as possible.
Tip 2 : Practice previous interview questions from internet.
Tip 3 : Revise Computer Science subjects like DBMS, OOPS thoroughly.
Tip 1 : Have some projects on resume.
Tip 2 : Do not put false things on resume.
First coding round as expected had some basic level DS Questions in bag.



A substring is a contiguous segment of a string.
You are given a string (STR) of length N.
Your task is to find the longest palindromic substring. If there is more than one palindromic substring with the maximum length, return the one with the smaller start index.
Note:
A substring is a contiguous segment of a string.
For Example :
The longest palindromic substring of "ababc" is "aba", since "aba" is a palindrome and it is the longest substring of length 3 which is a palindrome. There is another palindromic substring of length 3 is "bab". Since starting index of "aba" is less than "bab", so "aba" is the answer.
It was a coding round consisting of some DS questions and some ML Questions.


You are given a string ‘text’ and a string ‘pattern’, your task is to find all occurrences of pattern in the string ‘text’ and return an array of indexes of all those occurrences. You may assume that the length of ‘text’ is always greater than the length of ‘pattern’.
For Example :
Let text = “this is a good place to have a good start”, pattern = “good” so you have to return {10, 31} because at 10 and 31 index pattern is present in the text.
Note :
If there is no such index in the text then just return an array containing -1.
What is Naive Bayes used for?
Naive Bayes algorithms are mostly used in sentiment analysis, spam filtering, recommendation systems etc. They are fast and easy to implement but their biggest disadvantage is that the requirement of predictors to be independent.
Linear Regression vs Logistic Regression
Linear Regression is a machine learning algorithm based on supervised regression algorithm. Regression models a target prediction value based on independent variables. It is mostly used for finding out the relationship between variables and forecasting. Different regression models differ based on – the kind of relationship between the dependent and independent variables, they are considering and the number of independent variables being used.
Logistic regression is basically a supervised classification algorithm. In a classification problem, the target variable(or output), y, can take only discrete values for a given set of features(or inputs), X.

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Solving this problem will increase your chance to get selected in this company
What is recursion?