Handling Imbalanced Data in machine learning classification (Python) - 1

Показать описание

Welcome to our Handling Imbalanced Data in machine learning classification series. You'll work on a highly imbalanced example dataset in Python.

In this Part 1 video, we'll learn:
- what is imbalanced data
- what are the proper evaluation metrics for it
- set up our example of a highly imbalanced dataset ready for modeling.

Please check out the Part 2 video to learn 6 popular techniques to deal with the imbalanced data problem in Python.

✔️Collecting a bigger sample
✔️Oversampling (e.g., random, SMOTE)
✔️Undersampling (e.g., random, K-Means, Tomek links)
✔️Combining over and undersampling
✔️Weighing classes differently
✔️Changing algorithms

Technologies that will be used:
☑️ JupyterLab (Notebook)
☑️ pandas
☑️ sklearn
☑️ imbalanced-learn (imblearn)

Links mentioned in the video

Lianne and Justin
imbalanced data
imbalanced data machine learning
imbalanced data classification
python
smote

Рекомендации по теме

Handling Imbalanced Data in machine learning classification (Python) - 1

How to handle imbalanced datasets in Python

Handling imbalanced dataset in machine learning | Deep Learning Tutorial 21 (Tensorflow2.0 & Pyt...

Handling Imbalanced Dataset in Machine Learning: Easy Explanation for Data Science Interviews

Tutorial 45-Handling imbalanced Dataset using python- Part 1

Handling Imbalanced Data | Oversampling | Undersampling | SMOTE | Machine Learning | Data Science

What Is Balanced And Imbalanced Dataset How to handle imbalanced datasets in ML DM by Mahesh Huddar

Handling Imbalanced Dataset | Data Science | Python | Machine Learning

Live Discussion On Handling Imbalanced Dataset- Machine Learning

Wayfair Data Science Explains It All: Handling Imbalanced Data

5 ways to work with imbalanced data | Imbalanced dataset machine learning | Imbalanced data

148 - 7 techniques to work with imbalanced data for machine learning in python

Tomek links Algorithm – Undersampling to handle Imbalanced data in machine learning by Mahesh Huddar...

Handling Imbalanced Data in machine learning classification (Python) - 2

How to Handle Imbalanced Data in Machine Learning #shorts

SMOTE (Synthetic Minority Oversampling Technique) for Handling Imbalanced Datasets

This is why you should care about unbalanced data .. as a data scientist

Getting grip of handling imbalanced dataset

Handling Imbalanced Datasets SMOTE Technique

Handling Imbalanced Data in machine learning classification (Python) - 1

4.7. How to Handle imbalanced Dataset | Data Pre-Processing | Machine Learning Course

handling imbalanced data | machine learning project |data analysis |data science

Imbalanced Data in Machine Learning | Undersampling | Oversampling | SMOTE

Handling Imbalanced Datasets using Python | Smote, Upsampling and Downsampling | Satyajit Pattnaik

Handling Imbalanced Dataset Using Cost Sensitive Neural Networks- Credit Card Fraud Detection