Classification with Support Vector Machines
MP4 | Video: AVC 1920x1080 | Audio: AAC 44KHz 2ch | Duration: 1 Hour | 246 MB
Genre: eLearning | Language: English

Support Vector Machine (SVM) is a supervised learning technique for building regression and classification models, and it is one of the most popular learning algorithms used in machine learning. Common uses for it include face detection, image classification, handwriting recognition, and text categorization, and it tends to perform better on smaller datasets than other algorithms. Learn how to use scikit-learn to build sophisticated SVM models, and learn why SVM can often find relationships in data when other algorithms can't.


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