Handling Imbalanced Data Classification Problems
5.0 /5- Offered byCoursera
Handling Imbalanced Data Classification Problems at Coursera Overview
Handling Imbalanced Data Classification Problems
at Coursera
Learn how to select best evaluation metric for imbalanced datasets and data resampling techniques
Duration | 2 hours |
Start from | Start Now |
Total fee | ₹729 |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Go to Website  |
Credential | Certificate |
Handling Imbalanced Data Classification Problems at Coursera Highlights
Handling Imbalanced Data Classification Problems
at Coursera
- Get all learning materials, including the interactive workspace and final quiz
- Get instant access to the necessary software packages through Rhyme
- A split-screen video walkthrough of each step, from a subject-matter expert
- Ability to access your cloud desktop across six different sessions
- Earn a certification after completion
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Handling Imbalanced Data Classification Problems at Coursera Course details
Handling Imbalanced Data Classification Problems
at Coursera
Who should do this course?
- For learners who are based in the North America region
What are the course deliverables?
- Understand the business problem and the dataset to choose best evaluation metric for the problem
- Create imbalanced data classification model using SMOTE data resampling technique
- Compute to ROC curve and use to adjust probability threshold
More about this course
- Learn how to select best evaluation metric for imbalanced datasets and data resampling techniques like undersampling, oversampling and SMOTE before we use them for model building process
- At the end of the course you will understand and learn how to implement ROC curve and adjust probability threshold to improve selected evaluation metric of the model
Handling Imbalanced Data Classification Problems at Coursera Curriculum
Handling Imbalanced Data Classification Problems
at Coursera
Loading and understanding the dataset
Exploring the dataset
Evaluation metric selection
Creating a baseline model
Resampling techniques for imbalanced datasets
Implementing ROC curve
Adjusting probability threshold
Handling Imbalanced Data Classification Problems at Coursera Faculty details
Handling Imbalanced Data Classification Problems
at Coursera
Bhaskarjit Sarmah
Bhaskarjit Sarmah is a data scientist. He creates predictive models to solve business problems. He has built computer vision and NLP applications to solve customer problems in various domains
Handling Imbalanced Data Classification Problems at Coursera Admission Process
Handling Imbalanced Data Classification Problems
at Coursera
Important Dates
May 25, 2024
Course Commencement Date
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Handling Imbalanced Data Classification Problems at Coursera Students Ratings & Reviews
Handling Imbalanced Data Classification Problems
at Coursera
5/5
1 Rating- 4-51
K
Karteek Menda
Handling Imbalanced Data Classification Problems
Offered by Coursera
5
Other: Imbalance is one of the most important which is to be considered and this course has given me the space to rethnk on various types of handling those imbalances between the classes.
Reviewed on 26 Sep 2021Read More
View 1 Review
Handling Imbalanced Data Classification Problems
at Coursera
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