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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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3D Translation Example

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 Consider the effect of a translation in the x,y,z direction by -2, -4, and -6 respectively on the homogenous coordinate position vectors [1, 6, 4].  Solution. 3D Translation Matrix is given as: Here, Tx = -2, Ty = -4, and Tz = -6. As We know, 3D translation is performed as: Therefore, we got  New co-ordinates are [-1  2  -2 ]
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Three Dimensional Transformations and Viewing

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 Three Dimensional Transformations  Q. What is 3D Translation? A. Translation means shifting a point or moving the whole object. In 3D we need 3 Translatio factors. Translation Matrix for 3D:  Q. How to perform 3D Transformation? A.  To perform 3D Transformation. Multiply point with translation Matrix. Here, Q. What is 3D Scaling? A. Scaling changes the size of the object. Scaling in 3D is similar to scaling in 2D. The Matrix for 3D scaling transformation given as:
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