Preprocessing for Machine Learning in Python

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(3)

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Course Features

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Duration

4 hours

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Mobile, Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Intermediate

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Teaching Type

Self Paced

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Video Content

4 hours

Course Description

This course will teach you how to preprocess data. Preprocessing data is essential for any machine-learning project. Preprocessing is essential for importing, cleaning, and fitting your machine learning model. Preprocessing refers to standardizing your data in order to make your model fit. Learn how to create new features from the data in your dataset. A preprocessing exercise will be given to help you create a UFO sightings dataset that you can use for modeling.

Course Overview

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Virtual Labs

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International Faculty

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Post Course Interactions

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Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

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Cleaning Data in Python

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Supervised Learning with scikit-learn

What You Will Learn

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In this course you'll learn how to get your cleaned data ready for modeling

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You'll learn how to standardize your data so that it's in the right form for your model, create new features to best leverage the information in your dataset, and select the best features to improve your model fit

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Finally, you'll have some practice preprocessing by getting a dataset on UFO sightings ready for modeling

Course Instructors

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DataCamp Content Creator

Course Instructor

DataCamp offers interactive R, Python, Spreadsheets, SQL and shell courses. All on topics in data science, statistics, and machine learning. Learn from a team of expert teachers in the comfort of you...

Course Reviews

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