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Overview
Context
This Preprocessing for Machine Learning in Python course offered by Data Camp covers the basics of how and when to perform data preprocessing. This essential step in any machine learning project is when you get your 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.
Finally, you'll have some practice preprocessing by getting a dataset on UFO sightings ready for modeling.
Programme Structure
Chapters include:
- Data Preprocessing
- Feature Engineering
- Putting it all together
- Standardizing Data
- Selecting features for modeling
Key information
Duration
- Part-time
- 1 days
Start dates & application deadlines
You can apply for and start this programme anytime.
Language
English
Delivered
Online
Campus Location
- New York City, United States
Disciplines
Machine Learning View 213 other Short Courses in Machine Learning in United StatesWhat students do after studying
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Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
Prerequisites
- Cleaning Data in Python
- Supervised Learning with scikit-learn
Tuition Fees
Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.
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International Applies to you
Applies to youNon-residentsFree - Out-of-StateFree
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Domestic
Applies to youIn-StateFree
Additional Details
This course can be accessed for free with the Data Camp Premium or Teams subscriptions
Funding
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