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Machine Learning A-Z : Support Vector Machine with Python © /

Learn machine learning and support vector machine from scratch About This Video Learn how to use Pandas for data analysis Learn how to use sci-kit-learn for SVM using the Titanic dataset Learn about training data, testing data, and outliers In Detail This course is truly a step by step. In every new...

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Detalles Bibliográficos
Autor principal: Sciences, AI (Autor)
Autor Corporativo: Safari, an O'Reilly Media Company
Formato: Electrónico Video
Idioma:Inglés
Publicado: Packt Publishing, 2021.
Edición:1st edition.
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Descripción
Sumario:Learn machine learning and support vector machine from scratch About This Video Learn how to use Pandas for data analysis Learn how to use sci-kit-learn for SVM using the Titanic dataset Learn about training data, testing data, and outliers In Detail This course is truly a step by step. In every new video, we build on what has already been learned and move one extra step forward; then we assign you a small task that is solved in the beginning of the next video. This comprehensive course will be your guide to learning how to use the power of Python to train your machine such that your machine starts learning just like a human; based on that learning, your machine starts making predictions as well! We'll be using Python as the programming language in this course, which is the hottest language nowadays when we talk about machine learning. Python will be taught from a very basic level up to an advanced level so that any machine learning concept can be implemented. We'll also learn various steps of data preprocessing, which allows us to make data ready for machine learning algorithms. We'll learn all the general concepts of machine learning, which will be followed by the implementation of one of the most important ML algorithms- "Support Vector Machine". Each and every concept of SVM will be taught theoretically and implemented using Python
Descripción Física:1 online resource (1 video file, approximately 11 hr., 10 min.)
ISBN:9781801071833
1801071837