Hands On Training

Preprocessing for Machine Learning in Python

via

DataCamp

Course Features

Duration

4 hours

Delivery Method

Online

Available on

Limited Access

Accessibility

Mobile, Desktop, Laptop

Language

English

Subtitles

English

Level

Intermediate

Teaching Type

Self Paced

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

Virtual Labs

International Faculty

Post Course Interactions

Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

Supervised Learning with scikit-learn

Cleaning Data in Python

What You Will Learn

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

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

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

Course Content

Expand all sections

Module 1: Introduction to Data Preprocessing

Module 2: Standardizing Data

Module 3: Feature Engineering

Module 4: Selecting features for modeling

Course Instructors

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...