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Markov Chains || Step-By-Step || ~xRay Pixy

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Learn Markov Chains step-by-step using real-life examples. Video Chapters: Markov Chains 00:00 Introduction 00:19 Topics Covered 01:49 Markov Chains Applications 02:04 Markov Property 03:18 Example 1 03:54 States, State Space, Transition Probabilities 06:17 Transition Matrix 08:17 Example 02 09:17 Example 03 10:26 Example 04 12:25 Example 05 14:16 Example 06 16:49 Example 07 18:11 Example 08 24:56 Conclusion
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Software Engineering

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 Software Engineering 

Software Engineering: Software Engineering (S.E.) is a profession dedicated to the designs, implementation, and modification of software. Applications of Software Engineering are: 
  1. Re-engineering of software
  2. Software Testing
  3. Software Maintainance 
  4. Software Analysis
  5. Software Design
  6. Software Implementation
The objective of software engineering is to produce good quality software, on time and within budget. To obtain this objective it is very important to focus on Software Quality and Software Development Process.
Software Characteristics are: 
  1. Reusability of the components.
  2. Softwares are not manufactured as hardware. 
  3. In the Software development process, there is no wear-out phase.
  4. Software is fixable.
Software Life Cycle Models: Software life cycle means the time period when a software product is conceived and when the software product is no longer available for use. The software Life cycle includes different phases:
  1. Requirement Phase
  2. Design Phase
  3. Implementation Phase
  4. Testing Phase
  5. Installation Phase
  6. Operation and Maintenance Phase
  7. Retirement Phase 
Software Requirement - > Software Design - > Software Implementation - > Software Testing - > Software Installation - > Software Maintenance - > Software Retirement. 

Software life cycle models in software engineering are often known as Software Development Life cycle (S.D.L.C). Different software life cycle models are:
  1. The Waterfall Model
  2. Increment Process Models
  3. Evolutionary Process Model
  4. Prototyping Model
  5. Spiral Model
  6. COCOMO Model - Constructive Cost Estimation Model
COCOMO Model: COCOMO (Constructive Cost Estimation Model) is a heuristic estimation technique proposed by Boehm. According to Bohem, there are 3 categories for software development based on development complexity: 
  1. Organic - Application. 
  2. Semidetached - Utility.
  3. Embedded - System Programs.
Software cost estimation should be done through 3 stages: Basic COCOMO, Intermediate COCOMO, and Complete COCOMO. COCOMO models are useful for project Time and Cost estimation. 







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PARTICLE SWARM OPTIMIZATION ALGORITHM NUMERICAL EXAMPLE

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how is the LBP |Local Binary Pattern| values calculated? Step-by-Step with Example

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PSO Python Code || Particle Swarm Optimization in Python || ~xRay Pixy

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Grey Wolf Optimization Algorithm

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Bat algorithm Explanation Step by Step with example

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Grey Wolf Optimization Algorithm Numerical Example

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