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SVM overview support vector and hyperplanes

SVM overview support vector and hyperplanes

Example of data classification using centroids and K-means.

Example of data classification using centroids and K-means.

Hyperplane SVM example class separation classification problem

Hyperplane SVM example class separation classification problem

Clustering using KNN algorithm with different values of K. K is the number of neighbors. Each symbol is a different cluster data: the serrated line circle represents how far the algorithm can see.

Clustering using KNN algorithm with different values of K. K is the number of neighbors. Each symbol is a different cluster data: the serrated line circle represents how far the algorithm can see.

Example of data classification using centroids and K-means.

Example of data classification using centroids and K-means.

Example of data with and without labels: each color represents a cluster / class of data.

Example of data with and without labels: each color represents a cluster / class of data.

Example of clustering data: each dotted circle represents a cluster while the X is the collected data.

Example of clustering data: each dotted circle represents a cluster while the X is the collected data.

Confusion Matrix Iris Dataset Practical Example

Confusion Matrix Iris Dataset Practical Example

Example of PCA application in databases.

Example of PCA application in databases.

Example of data classification using centroids and K-means.

Example of data classification using centroids and K-means.

Example of data with and without labels: each color represents a cluster / class of data.

Example of data with and without labels: each color represents a cluster / class of data.

Linear and polynomial regression example using price and size of houses: price in y axis and size in square meters m2 on axis x. Linear and Logistic regression for math machine learning and statistics

Linear and polynomial regression example using price and size of houses: price in y axis and size in square meters m2 on axis x. Linear and Logistic regression for math machine learning and statistics

Linear and polynomial regression example using price and size of houses: price in y axis and size in square meters m2 on axis x. Linear and Logistic regression for math machine learning and statistics

Linear and polynomial regression example using price and size of houses: price in y axis and size in square meters m2 on axis x. Linear and Logistic regression for math machine learning and statistics

Example of anomaly using anomaly detection system

Example of anomaly using anomaly detection system

Plot using make circles lib Python

Plot using make circles lib Python

Example of uncorrelated data. Non correlated data.

Example of uncorrelated data. Non correlated data.

Example of high data correlation.

Example of high data correlation.

Example of data classification using centroids and K-means.

Example of data classification using centroids and K-means.

Example of linear and nonlinear data: green points are a cluster and the blue ones are another. Linear data can be separated by a line while non linear data can not.

Example of linear and nonlinear data: green points are a cluster and the blue ones are another. Linear data can be separated by a line while non linear data can not.

Example of linear and polynomial regression classification using Euclidian distance. Points is the real data, blue line is predicted polynomial model and red line is the linear predicted model.

Example of linear and polynomial regression classification using Euclidian distance. Points is the real data, blue line is predicted polynomial model and red line is the linear predicted model.

Decision three example using body data to predict healthy or not healthy people based on input data.

Decision three example using body data to predict healthy or not healthy people based on input data.

Plot Iris Dataset with features using SVM Python and vector supports

Plot Iris Dataset with features using SVM Python and vector supports

Plot Iris Dataset with features using SVM Python

Plot Iris Dataset with features using SVM Python

Example of linear and nonlinear data: green points are a cluster and the blue ones are another. Linear data can be separated by a line while non linear data can not.

Example of linear and nonlinear data: green points are a cluster and the blue ones are another. Linear data can be separated by a line while non linear data can not.

Classification clustering data plot based on age and tumor size. Circle and X are two different types of data, the line between them separate the clusters.

Classification clustering data plot based on age and tumor size. Circle and X are two different types of data, the line between them separate the clusters.

Describe how a system behavior when receive input data and expected output for machine learning and an intelligent program.

Describe how a system behavior when receive input data and expected output for machine learning and an intelligent program.