Information Technology
Hands on Training icon
Hands On Training
Hands on Training icon

Dimensionality Reduction in Python

Course Cover

5

(3)

compare button icon

$12

$6

49% OFF

Visit Course

Visit Course

Course Features

icon

Duration

4 hours

icon

Delivery Method

Online

icon

Available on

Limited Access

icon

Accessibility

Mobile, Desktop, Laptop

icon

Language

English

icon

Subtitles

English

icon

Level

Intermediate

icon

Teaching Type

Self Paced

icon

Video Content

4 hours

Course Description

High-dimensional datasets can be overwhelming. A new dataset would be easier to visualize than an existing one. If you have multiple dimensions, traditional visualization techniques may not work. High-dimensional data can be visualized using many visualization methods. These techniques will be covered in the course. There are many features that lack information in data. This is often due to a lack of variation or duplicates. These features will be removed from your data to allow you to focus on the more informative. These features may also be used to build a model. You might find that some of these features don't affect what you are trying predict. You will also learn how you can identify and remove non-essential features in order to reduce complexity. You will also learn how feature extraction can reduce dimensionality by calculating uncorrelated principal components.

Course Overview

projects-img

Virtual Labs

projects-img

International Faculty

projects-img

Post Course Interactions

projects-img

Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

check-card-img

Supervised Learning with scikit-learn

What You Will Learn

check-card-img

Understand the concept of reducing dimensionality in your data, and master the techniques to do so in Python

check-card-img

You’ll learn how to detect these features and drop them from the dataset so that you can focus on the informative ones

check-card-img

You’ll learn how to detect and drop these irrelevant features too, in order to reduce dimensionality and thus complexity

Course Instructors

Author Image

Jeroen Boeye

Machine Learning Engineer @ Faktion

Jeroen is a machine learning engineer working at Faktion, an AI company from Belgium. He uses both R and Python for his analyses and has a PhD background in computational biology. His experience most...
Author Image

Aleksandra Vercauteren

Senior Data Scientist - Head of NLP @ Faktion

After 6 years as a researcher in Theoretical Linguistics, I decided to radically change careers and became a data scientist. I did not let go of my linguistic background and specialised in Natural La...

Course Reviews

Average Rating Based on 3 reviews

5.0

100%

Course Cover

$12

$6

49% OFF

Visit Course

Visit Course