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Confusion Matrix with Real-Life Examples || Artificial Intelligence || ~...

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Learn about the Confusion Matrix with Real-Life Examples. A confusion matrix is a table that shows how well an AI model makes predictions. It compares the actual results with the predicted ones and tells which are right or wrong. It includes True Positive (TP), False Positive (FP), False Negative (FN), and True Negative (TN). Video Chapters: Confusion Matrix in Artificial Intelligence 00:00 Introduction 00:12 Confusion Matrix 03:48 Metrices Derived from Confusion Matrix 04:26 Confusion Matrix Example 1 05:44 Confusion Matrix Example 2 08:10 Confusion Matrix Real-Life Uses #artificialintelligence #machinelearning #confusionmatrix #algorithm #optimization #research #happylearning #algorithms #meta #optimizationtechniques #swarmintelligence #swarm #artificialintelligence #machinelearning
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Solving Transportation Problem ||Operations Research and Optimization|| ...

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Unit 1  - INTRODUCTION TO OPTIMIZATION ALGORITHMS Video Chapters: Optimization Techniques 00:00 Introduction 02:39 Optimization Statement 05:27 Constrained Optimization Problems 06:06 Constrained Optimization Methods 07:38 Transportation Problem 14:40 Unconstrained Optimization Problems 20:15 Conclusion 1. What is Optimization?      Optimization is the process of finding the best solution or set of solutions from a range of possible options, with the aim of maximizing or minimizing a particular objective function. The objective function is a mathematical expression that represents the quantity to be optimized, such as maximizing profit, minimizing cost, or achieving the highest performance. There are two main types of optimization problems: Maximization Problems: These involve finding the maximum value of an objective function. Examples : maximizing profit, revenue, efficiency, or any other desirable outcome. Minimization Problems: These involve ...
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