The document discusses different asymptotic notations used to characterize the complexity of algorithms: Big-O(O) notation provides an upper bound, Big-Omega(Ω) provides a lower bound, and Big-Theta(Θ) indicates the same order of growth. It defines each notation, explaining that Big-O represents f(n) growing less than or equal to g(n), Big-Omega represents f(n) growing greater than or equal to g(n), and Big-Theta represents f(n) growing equal to g(n). The document then discusses basics of probability theory, defining a sample space as the set of all possible outcomes of an experiment, with events being subsets of the sample space.
Introduction to Algorithms and Asymptotic NotationAmrinder Arora
Asymptotic Notation is a notation used to represent and compare the efficiency of algorithms. It is a concise notation that deliberately omits details, such as constant time improvements, etc. Asymptotic notation consists of 5 commonly used symbols: big oh, small oh, big omega, small omega, and theta.
PPT on Analysis Of Algorithms.
The ppt includes Algorithms,notations,analysis,analysis of algorithms,theta notation, big oh notation, omega notation, notation graphs
Algorithm and its Properties
Computational Complexity
TIME COMPLEXITY
SPACE COMPLEXITY
Complexity Analysis and Asymptotic notations.
Big-oh-notation (O)
Omega-notation (Ω)
Theta-notation (Θ)
The Best, Average, and Worst Case Analyses.
COMPLEXITY Analyses EXAMPLES.
Comparing GROWTH RATES
Big O notation is used in Computer Science to describe the performance or complexity of an algorithm. Big O specifically describes the worst-case scenario, and can be used to describe the execution time required or the space used (e.g. in memory or on disk) by an algorithm.
For further information
https://github.com/ashim888/dataStructureAndAlgorithm
References:
https://www.khanacademy.org/computing/computer-science/algorithms/asymptotic-notation/a/asymptotic-notation
http://web.mit.edu/16.070/www/lecture/big_o.pdf
https://rob-bell.net/2009/06/a-beginners-guide-to-big-o-notation/
https://justin.abrah.ms/computer-science/big-o-notation-explained.html
Algorithms Lecture 1: Introduction to AlgorithmsMohamed Loey
We will discuss the following: Algorithms, Time Complexity & Space Complexity, Algorithm vs Pseudo code, Some Algorithm Types, Programming Languages, Python, Anaconda.
Introduction to Algorithms and Asymptotic NotationAmrinder Arora
Asymptotic Notation is a notation used to represent and compare the efficiency of algorithms. It is a concise notation that deliberately omits details, such as constant time improvements, etc. Asymptotic notation consists of 5 commonly used symbols: big oh, small oh, big omega, small omega, and theta.
PPT on Analysis Of Algorithms.
The ppt includes Algorithms,notations,analysis,analysis of algorithms,theta notation, big oh notation, omega notation, notation graphs
Algorithm and its Properties
Computational Complexity
TIME COMPLEXITY
SPACE COMPLEXITY
Complexity Analysis and Asymptotic notations.
Big-oh-notation (O)
Omega-notation (Ω)
Theta-notation (Θ)
The Best, Average, and Worst Case Analyses.
COMPLEXITY Analyses EXAMPLES.
Comparing GROWTH RATES
Big O notation is used in Computer Science to describe the performance or complexity of an algorithm. Big O specifically describes the worst-case scenario, and can be used to describe the execution time required or the space used (e.g. in memory or on disk) by an algorithm.
For further information
https://github.com/ashim888/dataStructureAndAlgorithm
References:
https://www.khanacademy.org/computing/computer-science/algorithms/asymptotic-notation/a/asymptotic-notation
http://web.mit.edu/16.070/www/lecture/big_o.pdf
https://rob-bell.net/2009/06/a-beginners-guide-to-big-o-notation/
https://justin.abrah.ms/computer-science/big-o-notation-explained.html
Algorithms Lecture 1: Introduction to AlgorithmsMohamed Loey
We will discuss the following: Algorithms, Time Complexity & Space Complexity, Algorithm vs Pseudo code, Some Algorithm Types, Programming Languages, Python, Anaconda.
The Big Oh (O) is the most commonly used notation to express an algorism’s performance. The big Oh (O)
notation is a method of expressing the upper bound on the growth rate of an algorithm’s running time. In
other words we can say that it is the longest amount of time, an algorithm could possibly take to finish it
therefore the “big-Oh” or O-Notation is used for worst-case analysis of the algorithm.
The Big Omega () notation is a method of expressing the lower bound on the growth rate of an algorithm’s
running time. In other words we can say that it is the minimum amount of time, an algorithm could possibly
take to finish it therefore the “big-Omega” or -Notation is used for best-case analysis of the algorithm.
Unit 1: Fundamentals of the Analysis of Algorithmic Efficiency, Units for Measuring Running Time, PROPERTIES OF AN ALGORITHM, Growth of Functions, Algorithm - Analysis, Asymptotic Notations, Recurrence Relation and problems
The little Oh (o) notation is a method of expressing the an upper bound on the growth rate of an algorithm’s
running time which may or may not be asymptotically tight therefore little oh(o) is also called a loose upper
bound we use little oh (o) notations to denote upper bound that is asymptotically not tight.
Similar to Asymptotic notations(Big O, Omega, Theta ) (20)
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How to Split Bills in the Odoo 17 POS ModuleCeline George
Bills have a main role in point of sale procedure. It will help to track sales, handling payments and giving receipts to customers. Bill splitting also has an important role in POS. For example, If some friends come together for dinner and if they want to divide the bill then it is possible by POS bill splitting. This slide will show how to split bills in odoo 17 POS.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
How to Create Map Views in the Odoo 17 ERPCeline George
The map views are useful for providing a geographical representation of data. They allow users to visualize and analyze the data in a more intuitive manner.
Ethnobotany and Ethnopharmacology:
Ethnobotany in herbal drug evaluation,
Impact of Ethnobotany in traditional medicine,
New development in herbals,
Bio-prospecting tools for drug discovery,
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The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
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Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
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Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
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Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
This is a presentation by Dada Robert in a Your Skill Boost masterclass organised by the Excellence Foundation for South Sudan (EFSS) on Saturday, the 25th and Sunday, the 26th of May 2024.
He discussed the concept of quality improvement, emphasizing its applicability to various aspects of life, including personal, project, and program improvements. He defined quality as doing the right thing at the right time in the right way to achieve the best possible results and discussed the concept of the "gap" between what we know and what we do, and how this gap represents the areas we need to improve. He explained the scientific approach to quality improvement, which involves systematic performance analysis, testing and learning, and implementing change ideas. He also highlighted the importance of client focus and a team approach to quality improvement.
2. Asymptotic Notations
• Rate of Growth:
• The following notations are commonly use notations in performance
analysis and used to characterize the complexity of an algorithm:
• 1.Big–OH (O) 1,
• 2.Big–OMEGA ( ),
• 3.Big–THETA ( ) and
• 4.Little–OH (o)
3. Big–OH O (Upper Bound)
f(n) = O(g(n)), (pronounced order of or big oh), says that the growth rate of
f(n) is less than or equal (<) that of g(n).
Big ‘oh’: the function f(n)=O(g(n)) iff there exist positive constants c and no
such that f(n)≤c*g(n) for all n, n ≥ no.
4.
5. Big–OMEGA Ω (Lower Bound)
f(n) = Ω (g(n)) (pronounced omega), says that the growth rate of f(n) is
greater than or equal to (>) that of g(n).
Omega: the function f(n)=Ω(g(n)) iff there exist positive constants c and no
such that f(n) ≥ c*g(n) for all n, n ≥ no.
6. Big–THETA ө (Same order)
f(n) = ө (g(n)) (pronounced theta), says that the growth rate of f(n)
equals (=) the growth rate of g(n) [if f(n) = O(g(n)) and T(n) = ө
(g(n)].
Theta: the function f(n)=ө(g(n)) iff there exist positive constants
c1,c2 and no such that c1 g(n) ≤ f(n) ≤ c2 g(n) for all n, n ≥ no.
7.
8.
9.
10.
11.
12.
13. RANDOMIZED ALGORITHMS
Basics of probability Theory: Probability theory has the goal of
characterizing the out comes of natural or conceptual "experiments”.
set of all possible outcomes is known as the sample space S.
In this text we assume that S is finite (such a sample spaceis called a
discrete sample
space).An event E is a subset of the sample space S.If the sample space
Consists of n sample points t,hen thereare2n possibel events.