In this blog, we will learn about various process scheduling algorithms used in Operating System. We will learn about FCFS, SJF, SRTF, Round-Robin, Priority-based, Highest Response Ratio Next, Multilevel Queue, and Multilevel Feedback Queue scheduling.
In this blog, we will learn what an Operating System is and what are the goals of an Operating System. We will also learn the functionalities of an Operating System that helps in achieving the goal of the OS.
You are given a string S and its length L and you need to sort its characters based on their frequency. The characters in the output will be distinct and ordered based on their frequency in S, higher frequency comes first.
In this blog, we will learn about the Context Switching in the Operating System. We will learn all the steps involved in Context Switching and in the end, we will see the advantages and disadvantages of Context Switching also.
In this blog, we will learn the difference between Multiprogramming, Multiprocessing, and Multitasking. These terms come into play when we talk about our processes and the processors. Let's see the difference between these.
In this blog, we will learn about various types of times that we come across during using some CPU scheduling algorithms i.e. Burst time, Arrival time, Exit time, Response time, Waiting time, Turnaround time, and Throughput.
Given two strings S1 and S2 of size m and n respectively, you need to check whether the two strings are an anagram of each other or not. S1 is an anagram of S2 if the characters of S1 can be rearranged to form S2.
Given two integer arrays A and B of size m and n, respectively. We need to find the intersection of these two arrays. The intersection of two arrays is a list of distinct numbers which are present in both the arrays. The numbers in the intersection can be in any order.
Given two integer array A and B of size m and n(n <= m) respectively. We have to check whether B is a subset of A or not. An array B is a subset of another array A if each element of B is present in A. (There are no repeated elements in both the arrays)
Feature engineering is the process of using domain knowledge of the data to create features that make machine learning algorithms work. If feature engineering is done correctly, it increases the predictive power of machine learning algorithms by creating features from raw data that help facilitate the machine learning process. Feature Engineering is an art.
An open-source machine learning framework for everyone. As I believe, when we know the internals of a library, we can get the most out of it. And we feel much more confident while working with that library. Today, TensorFlow is being used by top companies like Google, Uber, Airbnb, Nvidia, Dropbox, etc.
All over the world, millions of students are looking forward to pursuing a career in the field of computer science. Though a lot of learning resources are available online, still, most of the students are struggling to become good at it and crack the interview.