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Overview
Context
Machine learning models are easier to implement now more than ever before. Without proper validation, the results of running new data through a model might not be as accurate as expected. Model validation allows analysts to confidently answer the question, how good is your model?
In this Model Validation in Python course offered by Data Camp, we will answer this question for classification models using the complete set of tic-tac-toe endgame scenarios, and for regression models using fivethirtyeight’s ultimate Halloween candy power ranking dataset.
Programme Structure
Chapters include:
- Basic Modeling in scikit-learn
- Cross Validation
- Validation Basics
- Selecting the best model with Hyperparameter tuning
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
- 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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