Chapter Name:Introduction To Algorithm
Topic 1.1 : What Is An Algorithm?
What Is An Algorithm? What are the criteria an algorithm must satisfy or describe the characteristics of an algorithm.
This document discusses fundamentals of algorithms including:
- What algorithms are and their evolution from Persian mathematicians.
- The process of designing algorithms including defining inputs, outputs, and order of instructions.
- The need for algorithms to be correct according to their specifications and methods for confirming correctness.
- Iterative design issues such as use of loops, efficiency considerations, and estimating execution time.
- Algorithmic strategies like divide and conquer, backtracking, dynamic programming, and heuristics.
An algorithm is a set of well-defined steps to solve a problem. It takes inputs, processes them according to the steps, and produces an output. An algorithm must be unambiguous, have a finite number of steps, and produce a solution. Characteristics include having zero or more inputs, at least one output, unambiguous steps, feasibility, and independence from programming language. Advantages are ease of understanding and breaking problems into smaller steps, while disadvantages include the time needed to write algorithms and difficulty showing branching and looping. Designing an algorithm requires defining the problem, constraints, inputs, outputs, and solution. Analysis can be done before or after implementation to determine time and space complexity.
Machine Learning With Logistic RegressionKnoldus Inc.
Machine learning is the subfield of computer science that gives computers the ability to learn without being programmed. Logistic Regression is a type of classification algorithm, based on linear regression to evaluate output and to minimize the error.
An algorithm is a step-by-step procedure to solve a problem using a finite number of instructions. To create an algorithm, it must have clear inputs and outputs, unambiguous steps that terminate in a finite number of steps, and each step must be feasible to carry out using paper and pencil. Algorithms use conditional patterns and comments to help with modifications. A flowchart provides a visual representation of an algorithm using blocks like start, stop, assignment, processing, input, output, and conditional statements to depict the sequencing and repetition of instructions.
An algorithm is defined as a step-by-step procedure to produce an output from given inputs. It must be unambiguous, have well-defined inputs and outputs, terminate after a finite number of steps, and be feasible with available resources. A sample algorithm is provided that increments a variable until it reaches a threshold.
Programming aids- Algorithm, Flowchart, Pseudocodes and Decision tableAnjali Technosoft
The document discusses algorithms and different ways to represent them, including through flowcharts, pseudocode, and decision tables. It provides examples of each representation type and explains the key components and steps in constructing a flowchart, pseudocode, and decision table to model an algorithm for determining a student's final grade.
The document discusses the phases of algorithm analysis and design. It begins by defining an algorithm as a finite set of instructions to carry out a sequence of operations. It then outlines the four main phases: 1) Design - identifying the problem and designing a solution using flowcharts or pseudocode. 2) Analyze - analyzing the efficiency of the designed algorithm. 3) Implement - coding the algorithm. 4) Experiment - testing the algorithm and improving its design. Examples are given of algorithms like directions to a home or adding two numbers. The document ends noting analysis of algorithms studies program performance, resources used, correctness, time/space efficiency, security, and other characteristics.
This document discusses the process of algorithm design and analysis. It outlines 9 key techniques for solving problems algorithmically: 1) Understanding the problem, 2) Ascertaining computational capabilities, 3) Determining exact or approximate solutions, 4) Choosing appropriate data structures, 5) Using algorithm design techniques, 6) Specifying the algorithm, 7) Proving correctness, 8) Analyzing efficiency, and 9) Coding the algorithm. These techniques provide a systematic approach to developing procedural solutions to problems through specific instructions to obtain answers.
Jagannath Institute Of Management Sciences, Vasant Kunj-II is one of the best BCA colleges in Delhi. Dr. Arpana Chaturvedi shares here the Notes of C- Algorithms. This subject is taught to semester I students of BCA
The document outlines a C++ programming problem that requires calculating the total amount of ringgit in savings based on user input of the quantities of RM1, RM5, RM10, and RM50 coins and bills. The problem requires 4 inputs - the quantities of each denomination, and has 1 output - the total amount in ringgit. An algorithm is described that would take the input quantities and convert them to an output total amount by multiplying each quantity by its denomination value and summing the results. The algorithm is tested on a sample input of 5 RM1 coins, 3 RM5 coins, 7 RM10 bills, and 4 RM50 bills to check that it works as intended.
This document outlines the course content and structure for a class on Fundamentals of Algorithms. It includes:
1. The prerequisites for the class which include programming experience and familiarity with data structures.
2. An overview of the purpose and evaluation scheme for the class, which focuses on analyzing and designing algorithms rather than programming. Student work will be evaluated through tests, assignments, and other activities.
3. A list of topics to be covered including analysis of algorithms, data structures like trees and graphs, sorting techniques, and others. Reference books are also provided.
The document discusses algorithms, including their definition, common types of algorithms, properties of algorithms, and how to write algorithms. It provides an example algorithm to add two numbers and explains how to analyze algorithms for efficiency in terms of time and space complexity. Time complexity represents the running time of an algorithm, while space complexity represents the memory required.
Lecture Note-2: Performance analysis of AlgorithmsRajesh K Shukla
The execution of an algorithm requires various resources of the computer system to complete the task. The
performance of algorithms depends on the use of these resources. The important resources which contribute
to the efficiency of the algorithms are the memory space and the time required for successful execution of
algorithm. The efficiency of an algorithm is measured in terms of the time and the space required for its
execution therefore analysis of algorithms is divided into two categories
Algorithm and flowchart with pseudo codehamza javed
1. Initialize the biggest price to the first price in the list
2. Loop through the remaining 99 prices
3. Compare each price to the biggest and update biggest if greater
4. After the loop, reduce the biggest price by 10%
5. Output the reduced biggest price
An algorithm is a step-by-step process for solving a problem or completing a task. There are two main tools used to document algorithms: flowcharts and pseudocode. A flowchart is a graphical representation of an algorithm that uses standardized symbols to show the sequence of steps, while pseudocode specifies the algorithm steps using natural language. The five steps in using a computer as a problem-solving tool are: developing an algorithm and flowchart, writing the program code, entering the program into the computer, testing and debugging the program, and running the program to obtain results.
The document discusses algorithms, defining them as logical sequences of steps to solve problems and listing properties of good algorithms such as being simple, complete, correct, and having appropriate abstraction. It also provides examples of algorithms and outlines steps for developing algorithms, including analyzing the problem, designing a solution, implementing the program, testing it, and validating it works for all cases.
This document discusses flowcharts and pseudocode as tools for problem solving and programming. It provides examples of how to represent algorithms using flowcharts and pseudocode. Flowcharts graphically show the logical steps and relationships between steps to solve a problem. Pseudocode uses English-like phrases to outline the steps. The document gives examples of flowcharts and pseudocode for problems like calculating postage for letters and finding a class average grade. It also discusses basic flowchart symbols and programming structures like sequence, decision, and looping.
This document provides an overview of the Design & Analysis of Algorithms course. The course aims to develop proficiency in problem solving, programming, and analyzing algorithms for time and space complexity. Students will learn to select appropriate data structures and algorithms for problems, and compare algorithms' complexities. The course covers topics like asymptotic analysis, divide-and-conquer, dynamic programming, cryptography, geometric algorithms, and parallel/distributed algorithms. Evaluation includes midterm and final exams, assignments, and class participation. Regular attendance is expected and required to avoid debarment.
This document introduces algorithms and their characteristics. It discusses the two phases of programming as problem solving and implementation. It covers understanding the problem, designing the algorithm, proving correctness, analyzing complexity, and coding the algorithm. Common algorithm design techniques like divide-and-conquer, greedy methods, and dynamic programming are presented. The document also discusses representing algorithms in pseudocode and natural language, and analyzing worst-case, average-case, and best-case complexity.
Logistic regression : Use Case | Background | Advantages | DisadvantagesRajat Sharma
This slide will help you to understand the working of logistic regression which is a type of machine learning model along with use cases, pros and cons.
An algorithm is a set of step-by-step instructions to solve a problem or complete a task. It must specify all steps clearly so a computer can follow the algorithm without additional understanding. Algorithms can be represented as pseudocode, a written informal description, or as a flowchart using graphical symbols. The key phases of an algorithm are problem solving to design the steps, then implementation in a programming language. Properties of good algorithms include being correct, efficient, and working for all possible inputs to the problem.
This document discusses algorithms and flowcharts. It provides an example of creating an algorithm to find the largest of two numbers and representing it as a flowchart. It also includes contact information for Baabtra-Mentoring Partner, the division of Baabtra System Technologies that provides mentoring programs.
This document discusses algorithm design and provides information on various algorithm design techniques. It begins with definitions of an algorithm and algorithm design. It then discusses the importance of algorithm design and some common algorithm design techniques including dynamic programming, graph algorithms, divide and conquer, backtracking, greedy algorithms, and using flowcharts. It also provides brief descriptions and examples of each technique. The document concludes by listing some advantages of designing algorithms such as ease of use, performance, scalability, and stability.
01 Introduction to analysis of Algorithms.pptxssuser586772
An algorithm is a set of steps of operations to solve a problem performing calculation, data processing, and automated reasoning tasks.
An algorithm is an efficient method that can be expressed within finite amount of Time and space.
The important aspects of algorithm design include creating an efficient algorithm to solve a problem in an efficient way using minimum time and space.
To solve a problem, different approaches can be followed. Some of them can be efficient with respect to time consumption, whereas other approaches may be memory efficient. To Evaluate An Algorithm we have to Satisfy the following Criteria:
INPUT: The Algorithm should be given zero or more input.
OUTPUT: At least one quantity is produced. For each input the algorithm produced value from specific task.
DEFINITENESS: Each instruction is clear and unambiguous.
FINITENESS: If we trace out the instructions of an algorithm, then for all cases, the algorithm terminates after a finite number of steps.
EFFECTIVENESS: Every instruction must very basic so that it can be carried out, in principle, by a person using only pencil & paper.Algorithm : Systematic logical approach which is a well-defined, step-by-step procedure that allows a computer to solve a problem.
Pseudocode : It is a simpler version of a programming code in plain English which uses short phrases to write code for a program before it is implemented in a specific programming language.
Program : It is exact code written for problem following all the rules of the programming language.Algorithm can be described (Represent) in four ways.
Natural language like English:
When this way is chooses, care should be taken, we
should ensure that each & every statement is definite.
(no ambiguity)
2. Graphic representation called flowchart:
This method will work well when the algorithm is small& simple.
3. Pseudo-code Method:
In this method, we should typically describe algorithms as
program, which resembles language like Pascal & Algol
(Algorithmic Language).
4.Programming Language:
we have to use programming language to write algorithms like
C, C++,JAVA etc.Comments begin with // and continue until the end of line.
Blocks are indicated with matching braces { and }.
An identifier begins with a letter. The data types of variables are not explicitly declared.
node= record
{
data type 1 data 1;
data type n data n;
node *link;
}
4. There are two Boolean values TRUE and FALSE.
Logical Operators
AND, OR, NOT
Relational Operators
<, <=,>,>=, =, !=
1.How to create an algorithm: To create an algorithm we have following design technique
a) Divide & Conquer
b) Greedy method
c) Dynamic Programming
d) Branch & Bound
e) Backtracking
2.How to validate an algorithm:
Once an algorithm is created it is necessary to show that it computes the correct Pr
The document provides an introduction to algorithms and their analysis. It defines an algorithm and lists its key criteria. It discusses different representations of algorithms including flowcharts and pseudocode. It also outlines the main areas of algorithm analysis: devising algorithms, validating them, analyzing performance, and testing programs. Finally, it provides examples of algorithms and their analysis including calculating time complexity based on counting operations.
An algorithm is a tool for solving any computational problem. It may be defined as a sequence of finite,
precise and unambiguous instructions which are applied either to perform a computation or to solve a
computational problem. These instructions are applied on some raw data called the input, and the
solution of the problem produced is called the output.
The document discusses the phases of algorithm analysis and design. It begins by defining an algorithm as a finite set of instructions to carry out a sequence of operations. It then outlines the four main phases: 1) Design - identifying the problem and designing a solution using flowcharts or pseudocode. 2) Analyze - analyzing the efficiency of the designed algorithm. 3) Implement - coding the algorithm. 4) Experiment - testing the algorithm and improving its design. Examples are given of algorithms like directions to a home or adding two numbers. The document ends noting analysis of algorithms studies program performance, resources used, correctness, time/space efficiency, security, and other characteristics.
This document discusses the process of algorithm design and analysis. It outlines 9 key techniques for solving problems algorithmically: 1) Understanding the problem, 2) Ascertaining computational capabilities, 3) Determining exact or approximate solutions, 4) Choosing appropriate data structures, 5) Using algorithm design techniques, 6) Specifying the algorithm, 7) Proving correctness, 8) Analyzing efficiency, and 9) Coding the algorithm. These techniques provide a systematic approach to developing procedural solutions to problems through specific instructions to obtain answers.
Jagannath Institute Of Management Sciences, Vasant Kunj-II is one of the best BCA colleges in Delhi. Dr. Arpana Chaturvedi shares here the Notes of C- Algorithms. This subject is taught to semester I students of BCA
The document outlines a C++ programming problem that requires calculating the total amount of ringgit in savings based on user input of the quantities of RM1, RM5, RM10, and RM50 coins and bills. The problem requires 4 inputs - the quantities of each denomination, and has 1 output - the total amount in ringgit. An algorithm is described that would take the input quantities and convert them to an output total amount by multiplying each quantity by its denomination value and summing the results. The algorithm is tested on a sample input of 5 RM1 coins, 3 RM5 coins, 7 RM10 bills, and 4 RM50 bills to check that it works as intended.
This document outlines the course content and structure for a class on Fundamentals of Algorithms. It includes:
1. The prerequisites for the class which include programming experience and familiarity with data structures.
2. An overview of the purpose and evaluation scheme for the class, which focuses on analyzing and designing algorithms rather than programming. Student work will be evaluated through tests, assignments, and other activities.
3. A list of topics to be covered including analysis of algorithms, data structures like trees and graphs, sorting techniques, and others. Reference books are also provided.
The document discusses algorithms, including their definition, common types of algorithms, properties of algorithms, and how to write algorithms. It provides an example algorithm to add two numbers and explains how to analyze algorithms for efficiency in terms of time and space complexity. Time complexity represents the running time of an algorithm, while space complexity represents the memory required.
Lecture Note-2: Performance analysis of AlgorithmsRajesh K Shukla
The execution of an algorithm requires various resources of the computer system to complete the task. The
performance of algorithms depends on the use of these resources. The important resources which contribute
to the efficiency of the algorithms are the memory space and the time required for successful execution of
algorithm. The efficiency of an algorithm is measured in terms of the time and the space required for its
execution therefore analysis of algorithms is divided into two categories
Algorithm and flowchart with pseudo codehamza javed
1. Initialize the biggest price to the first price in the list
2. Loop through the remaining 99 prices
3. Compare each price to the biggest and update biggest if greater
4. After the loop, reduce the biggest price by 10%
5. Output the reduced biggest price
An algorithm is a step-by-step process for solving a problem or completing a task. There are two main tools used to document algorithms: flowcharts and pseudocode. A flowchart is a graphical representation of an algorithm that uses standardized symbols to show the sequence of steps, while pseudocode specifies the algorithm steps using natural language. The five steps in using a computer as a problem-solving tool are: developing an algorithm and flowchart, writing the program code, entering the program into the computer, testing and debugging the program, and running the program to obtain results.
The document discusses algorithms, defining them as logical sequences of steps to solve problems and listing properties of good algorithms such as being simple, complete, correct, and having appropriate abstraction. It also provides examples of algorithms and outlines steps for developing algorithms, including analyzing the problem, designing a solution, implementing the program, testing it, and validating it works for all cases.
This document discusses flowcharts and pseudocode as tools for problem solving and programming. It provides examples of how to represent algorithms using flowcharts and pseudocode. Flowcharts graphically show the logical steps and relationships between steps to solve a problem. Pseudocode uses English-like phrases to outline the steps. The document gives examples of flowcharts and pseudocode for problems like calculating postage for letters and finding a class average grade. It also discusses basic flowchart symbols and programming structures like sequence, decision, and looping.
This document provides an overview of the Design & Analysis of Algorithms course. The course aims to develop proficiency in problem solving, programming, and analyzing algorithms for time and space complexity. Students will learn to select appropriate data structures and algorithms for problems, and compare algorithms' complexities. The course covers topics like asymptotic analysis, divide-and-conquer, dynamic programming, cryptography, geometric algorithms, and parallel/distributed algorithms. Evaluation includes midterm and final exams, assignments, and class participation. Regular attendance is expected and required to avoid debarment.
This document introduces algorithms and their characteristics. It discusses the two phases of programming as problem solving and implementation. It covers understanding the problem, designing the algorithm, proving correctness, analyzing complexity, and coding the algorithm. Common algorithm design techniques like divide-and-conquer, greedy methods, and dynamic programming are presented. The document also discusses representing algorithms in pseudocode and natural language, and analyzing worst-case, average-case, and best-case complexity.
Logistic regression : Use Case | Background | Advantages | DisadvantagesRajat Sharma
This slide will help you to understand the working of logistic regression which is a type of machine learning model along with use cases, pros and cons.
An algorithm is a set of step-by-step instructions to solve a problem or complete a task. It must specify all steps clearly so a computer can follow the algorithm without additional understanding. Algorithms can be represented as pseudocode, a written informal description, or as a flowchart using graphical symbols. The key phases of an algorithm are problem solving to design the steps, then implementation in a programming language. Properties of good algorithms include being correct, efficient, and working for all possible inputs to the problem.
This document discusses algorithms and flowcharts. It provides an example of creating an algorithm to find the largest of two numbers and representing it as a flowchart. It also includes contact information for Baabtra-Mentoring Partner, the division of Baabtra System Technologies that provides mentoring programs.
This document discusses algorithm design and provides information on various algorithm design techniques. It begins with definitions of an algorithm and algorithm design. It then discusses the importance of algorithm design and some common algorithm design techniques including dynamic programming, graph algorithms, divide and conquer, backtracking, greedy algorithms, and using flowcharts. It also provides brief descriptions and examples of each technique. The document concludes by listing some advantages of designing algorithms such as ease of use, performance, scalability, and stability.
01 Introduction to analysis of Algorithms.pptxssuser586772
An algorithm is a set of steps of operations to solve a problem performing calculation, data processing, and automated reasoning tasks.
An algorithm is an efficient method that can be expressed within finite amount of Time and space.
The important aspects of algorithm design include creating an efficient algorithm to solve a problem in an efficient way using minimum time and space.
To solve a problem, different approaches can be followed. Some of them can be efficient with respect to time consumption, whereas other approaches may be memory efficient. To Evaluate An Algorithm we have to Satisfy the following Criteria:
INPUT: The Algorithm should be given zero or more input.
OUTPUT: At least one quantity is produced. For each input the algorithm produced value from specific task.
DEFINITENESS: Each instruction is clear and unambiguous.
FINITENESS: If we trace out the instructions of an algorithm, then for all cases, the algorithm terminates after a finite number of steps.
EFFECTIVENESS: Every instruction must very basic so that it can be carried out, in principle, by a person using only pencil & paper.Algorithm : Systematic logical approach which is a well-defined, step-by-step procedure that allows a computer to solve a problem.
Pseudocode : It is a simpler version of a programming code in plain English which uses short phrases to write code for a program before it is implemented in a specific programming language.
Program : It is exact code written for problem following all the rules of the programming language.Algorithm can be described (Represent) in four ways.
Natural language like English:
When this way is chooses, care should be taken, we
should ensure that each & every statement is definite.
(no ambiguity)
2. Graphic representation called flowchart:
This method will work well when the algorithm is small& simple.
3. Pseudo-code Method:
In this method, we should typically describe algorithms as
program, which resembles language like Pascal & Algol
(Algorithmic Language).
4.Programming Language:
we have to use programming language to write algorithms like
C, C++,JAVA etc.Comments begin with // and continue until the end of line.
Blocks are indicated with matching braces { and }.
An identifier begins with a letter. The data types of variables are not explicitly declared.
node= record
{
data type 1 data 1;
data type n data n;
node *link;
}
4. There are two Boolean values TRUE and FALSE.
Logical Operators
AND, OR, NOT
Relational Operators
<, <=,>,>=, =, !=
1.How to create an algorithm: To create an algorithm we have following design technique
a) Divide & Conquer
b) Greedy method
c) Dynamic Programming
d) Branch & Bound
e) Backtracking
2.How to validate an algorithm:
Once an algorithm is created it is necessary to show that it computes the correct Pr
The document provides an introduction to algorithms and their analysis. It defines an algorithm and lists its key criteria. It discusses different representations of algorithms including flowcharts and pseudocode. It also outlines the main areas of algorithm analysis: devising algorithms, validating them, analyzing performance, and testing programs. Finally, it provides examples of algorithms and their analysis including calculating time complexity based on counting operations.
An algorithm is a tool for solving any computational problem. It may be defined as a sequence of finite,
precise and unambiguous instructions which are applied either to perform a computation or to solve a
computational problem. These instructions are applied on some raw data called the input, and the
solution of the problem produced is called the output.
This document discusses algorithms and flowcharts. It defines an algorithm as a set of steps to solve a problem, especially by a computer. Algorithms have inputs, outputs, and must be unambiguous, finite, effective, and language-independent. Flowcharts provide a graphical representation of algorithms using standard symbols connected by arrows to show the flow. The document gives examples of algorithms to add two numbers and provides a flowchart to multiply two numbers as illustrations.
INTRODUCTION TO ALGORITHM in MATHEMATICAL PROBLEM SOLVINGSwastiSwagat
This document introduces algorithms and discusses their key characteristics and phases. It defines an algorithm as a sequence of unambiguous instructions to solve a problem within a finite amount of time. The main characteristics are that algorithms must be finite, definite, accept inputs, produce outputs, and be effective. The four phases of algorithms are design, validation, analysis, and testing. Algorithm design techniques include divide and conquer, incremental approach, dynamic programming, and greedy algorithms. Validation checks the logic and behavior. Analysis determines time and space complexity. Testing debugs and measures performance.
This document provides an introduction to algorithms including definitions, characteristics, and the design process. It defines an algorithm as a finite set of unambiguous instructions to solve a problem. Key points:
- Algorithms must have input, output, be definitive, finite, and effective.
- The design process includes understanding the problem, developing a solution algorithm, proving correctness, analyzing efficiency, and coding.
- Examples of algorithm types are approximate, probabilistic, infinite, and heuristic.
- Pseudocode is commonly used to specify algorithms more clearly than natural language alone.
The document provides an overview of algorithms, including definitions, types, characteristics, and analysis. It begins with step-by-step algorithms to add two numbers and describes the difference between algorithms and pseudocode. It then covers algorithm design approaches, characteristics, classification based on implementation and logic, and analysis methods like a priori and posteriori. The document emphasizes that algorithm analysis estimates resource needs like time and space complexity based on input size.
This document outlines the syllabus for the subject "Design and Analysis of Algorithms" for the 3rd year 1st semester students of the Computer Science and Engineering department with specialization in Cyber Security at CMR Engineering College.
The syllabus is divided into 5 units which cover topics like algorithm analysis, asymptotic notations, algorithm design techniques like divide and conquer, dynamic programming, greedy algorithms etc. It also discusses NP-hard and NP-complete problems. The document provides the textbook and references for the subject. It further includes introductions to different units explaining key concepts like algorithms, properties of algorithms, ways to represent algorithms, need for algorithm analysis etc.
Introduction to Design Algorithm And Analysis.pptBhargaviDalal4
This document contains the syllabus for the subject "Design and Analysis of Algorithms" for the 3rd year 1st semester students of CMR Engineering College. It includes 5 units - Introduction, Disjoint Sets and Backtracking, Dynamic Programming and Greedy Methods, Branch and Bound, and NP-Hard and NP-Complete problems. The introduction covers topics like algorithm complexity analysis and divide and conquer algorithms. The syllabus outlines core algorithms topics and applications like binary search, quicksort, dynamic programming, shortest paths, knapsack etc. that will be covered in the course.
PRESENTATION 0N ALGORITHM AND FLOWCHART.pptxbkumar2974
This document summarizes a presentation on algorithms and flowcharts. It defines an algorithm as a step-by-step solution to a problem and provides an example algorithm for adding two numbers. It describes the properties of algorithms including inputs, outputs, definiteness, effectiveness and finiteness. The document then defines a flowchart as the graphical representation of an algorithm using standard symbols. It discusses the complexity, merits and demerits of algorithms and flowcharts before concluding that a flowchart pictorial represents an algorithm.
The step by step solution for solving a problem is called an algorithm.
It is a finite set of instruction which is used for a particular task.
An algorithm is defined as computational procedure that takes some input value or set of input values and produce the output.
A sequential solution of any problem
Written in human understandable form
This document provides an overview of algorithms. It begins by discussing the origins and evolution of the term "algorithm" from its Arabic roots in the 9th century to its modern meaning of a well-defined computational procedure. The document then defines algorithms and their key characteristics such as being precise, unambiguous, and terminating after a finite number of steps. Common algorithm design techniques like divide-and-conquer, greedy algorithms, and dynamic programming are introduced. Examples of merge sort and finding the maximum element in a list are used to illustrate algorithm concepts.
This document discusses algorithms including:
- An algorithm is a set of instructions to accomplish a task, with inputs and outputs.
- Characteristics of algorithms include being definite, finite, unambiguous, and efficient.
- The design process involves understanding the problem, capabilities of the device, choosing exact or approximate solutions, selecting a data structure, and techniques like divide-and-conquer.
- Algorithms can be specified through languages, pseudocode, or flowcharts and must be proven correct. Their analysis considers time and space complexity.
Transform tomorrow: Master benefits analysis with Gen AI today webinar
Wednesday 30 April 2025
Joint webinar from APM AI and Data Analytics Interest Network and APM Benefits and Value Interest Network
Presenter:
Rami Deen
Content description:
We stepped into the future of benefits modelling and benefits analysis with this webinar on Generative AI (Gen AI), presented on Wednesday 30 April. Designed for all roles responsible in value creation be they benefits managers, business analysts and transformation consultants. This session revealed how Gen AI can revolutionise the way you identify, quantify, model, and realised benefits from investments.
We started by discussing the key challenges in benefits analysis, such as inaccurate identification, ineffective quantification, poor modelling, and difficulties in realisation. Learnt how Gen AI can help mitigate these challenges, ensuring more robust and effective benefits analysis.
We explored current applications and future possibilities, providing attendees with practical insights and actionable recommendations from industry experts.
This webinar provided valuable insights and practical knowledge on leveraging Gen AI to enhance benefits analysis and modelling, staying ahead in the rapidly evolving field of business transformation.
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All of this is not just about what’s broken; it’s about what can be done. The talk concludes with providing a roadmap for rethinking the culture of creative industries and offers strategies for balancing passion with sustainability.
With this book and presentation I hope to challenge us to imagine a healthier future for the labor of love that a creative career is.
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Redesigning Education as a Cognitive Ecosystem: Practical Insights into Emerg...Leonel Morgado
Ad
Introduction To Algorithms
1. Chapter Name:
Introduction To Algorithm
Topic 1.1 :
What Is An Algorithm?
Project Prepared By:
KM Bappi
CSE 2006-2007
2. Q: What Is An Algorithm? What are the criteria an algorithm must
satisfy or describe the characteristics of an algorithm.
Answers :
An Algorithm is a process or set of rules to be followed in calculations or other problem-solving operations, especially by a computer.
In mathematics and computer science, an algorithm is a step-by-step procedure for calculations. Algorithms are used or calculation, data processing,
and automated reasoning.
An algorithm is an effective method expressed as a finite list of well-defined instructions for calculating a function. Starting from an initial
state and initial input the instructions describe a computation that, when executed, proceeds through a finite number of well-defined successive states,
eventually producing "output" and terminating at a final ending state.
Criteria:
i. Input:
Zero or more quantities or quire should be inputted externally.
ii. Output:
At least one quantities should be produced.
iii. Definiteness:
Each instruction is clear and definite.
iv. Finiteness:
For n terms of cases the algorithm should terminate it’s process after n terms.
v. Effectiveness:
Must be very basic and feasible.