Knowledge in Data Structures & algorithms
DATA STRUCTURE AND ALGORITHM with QUESTIONS AND ANSWERS
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DATA STRUCTURE AND ALGORITHM with QUESTIONS AND ANSWERS :(26 Attachments) Algorithm And Complexity :(1 Attachment) Data Structure Q&A :(5 Attachments) ALGORITHMS ANALYSIS AND ORDERS OF GROWTH :(3 Attachments) Computer Science Advanced INTERVIEW Q&A :(2 Attachments) GRAPHS DATA STRUCTURES :(2 Attachments) DESIGN AND ANALYSIS OF ALGORITHMS Quest And Answ :(7 Attachments) Wondering what is asked in the exam of data structure? You are at the right place, we can provide you with the solution to this problem. The below attatched pdf contains relevant question and answers that can be asked during the data sturucture exam. course - computer science, subject- Data Structures & algorithms.
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GRAPHS DATA STRUCTURES
Sharing the notes of GRAPHS DATA STRUCTURES in this Attachment.
Complexity of algorithm
what does complexity mean for a program? find out in this clip.
Design and analysis of algorithms(topic-wise)(ADA)
The Attatchment includes topics of design and analysis of algorithms, such as -Introduction, Complexity of algo, Asymptotic Notation, Finding function in asymptotic notation, Master's Theorem, Finding Complexity, Divide and Conquer intro, Intro to Greedy, Knapsack, Job Sequencing, Minimum Cost Spanning tree, Prims Algo, Kruskal algo, 0/1 Knapsack, Travelling Salesperson, Multistage Graph, Back Tracking, N Queen, M colorability and 15 puzzle
Data structure and Sorting techniques
Topics- Linear search,binary search,(sorting insertion,merge,selection,radix) double linklist, linklist,divide and conquer, time and space complexity,circular queue,polish notation, insertion and deletion from a linklist.
Anuradha Bhatia
Decision Trees for Uncertain Data
Available below are the notes for the course Computer Science and subject Data Structures & algorithms. The topics discussed in the document attatched below are EXISTING SYSTEM, ABSTRACT, PROPOSED SYSTEM, Data Insertion, Generate Tree, Averaging, etc.
Ajay Kuwarbi
Importance of choosing the right algorithm
Importance of choosing the right algorithm Yesterday, I saw a movie called ” Edge of tomorrow“. I loved the concept and the thought process which went behind the plot of this movie. Let me summarize the plot (without commenting on the climax, of course). Unlike other sci-fi movies, this movie revolves around one single power which is given to both the sides (hero and villain). The power being the ability to reset the day. Human race is at war with an alien species called “Mimics”. Mimic is described as a far more evolved civilization of an alien species. Entire Mimic civilization is like a single complete organism. It has a central brain called “Omega” which commands all other organisms in the civilization. It stays in contact with all other species of the civilization every single second. “Alpha” is the main warrior species (like the nervous system) of this civilization and takes command from “Omega”. “Omega” has the power to reset the day at any point of time. Now, let’s wear the hat of a predictive analyst to analyze this plot. If a system has the ability to reset the day at any point of time, it will use this power, whenever any of its warrior species die. And, hence there will be no single war ,when any of the warrior species (alpha) will actually die, and the brain “Omega” will repeatedly test the best case scenario to maximize the death of human race and put a constraint on number of deaths of alpha (warrior species) to be zero every single day. You can imagine this as “THE BEST” predictive algorithm ever made. It is literally impossible to defeat such an algorithm.
tulika goyal
Dimensionality Reduction Algorithms
Dimensionality Reduction Algorithms In the last 4-5 years, there has been an exponential increase in data capturing at every possible stages. Corporates/ Government Agencies/ Research organisations are not only coming with new sources but also they are capturing data in great detail. For example: E-commerce companies are capturing more details about customer like their demographics, web crawling history, what they like or dislike, purchase history, feedback and many others to give them personalized attention more than your nearest grocery shopkeeper. As a data scientist, the data we are offered also consist of many features, this sounds good for building good robust model but there is a challenge. How’d you identify highly significant variable(s) out 1000 or 2000? In such cases, dimensionality reduction algorithm helps us along with various other algorithms like Decision Tree, Random Forest, PCA, Factor Analysis, Identify based on correlation matrix, missing value ratio and others. To know more about this algorithms, you can read “Beginners Guide To Learn Dimension Reduction Techniques“.
Design And Analysis of algorithm
CoEP complete content for DAA semester 5th Department CSIT
Shubham Kankutlawar
linked list
it covers linked list, stack and queue
shivam Agarwal
DATASYSTEM AND GRAPHICS THEORY
CoEP Year 2nd Dept Comp DATASTRUCTURE AND GRAPHICS THEORY
Gaurav Mutyalwar
INTRODUCTION TO THEORY OF COMPUTATION
CoEP Year 2nd Dept Comp INTRODUCTION TO THEORY OF COMPUTATION