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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Bibliographic Details
Main Author: Sciences, AI
Format: eBook
Language:English
Published: Packt Publishing 2021
Edition:1st edition
Subjects:
Online Access:
Collection: O'Reilly - Collection details see MPG.ReNa
Description
Summary: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
Item Description:Made available through: Safari, an O'Reilly Media Company
Physical Description:1 video file, approximately 11 hr., 10 min.
ISBN:9781801071833