Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
612-822-4611

  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Machine Learning for Imbalanced Data: Tackle imbalanced datasets using machine learning and deep learning techniques

Machine Learning for Imbalanced Data: Tackle imbalanced datasets using machine learning and deep learning techniques

Abhishek, Kumar
Abdelaziz, Mounir

Paperback

General Computers

ISBN10: 1801070830
ISBN13: 9781801070836
Publisher: Packt Pub
Published: Nov 30 2023
Pages: 344
Weight: 1.30
Height: 0.72 Width: 7.50 Depth: 9.25
Language: English

Take your machine learning expertise to the next level with this essential guide, utilizing libraries like imbalanced-learn, PyTorch, scikit-learn, pandas, and NumPy to maximize model performance and tackle imbalanced data

Key Features
  • Understand how to use modern machine learning frameworks with detailed explanations, illustrations, and code samples
  • Learn cutting-edge deep learning techniques to overcome data imbalance
  • Explore different methods for dealing with skewed data in ML and DL applications
  • Purchase of the print or Kindle book includes a free eBook in the PDF format
Book Description

As machine learning practitioners, we often encounter imbalanced datasets in which one class has considerably fewer instances than the other. Many machine learning algorithms assume an equilibrium between majority and minority classes, leading to suboptimal performance on imbalanced data. This comprehensive guide helps you address this class imbalance to significantly improve model performance.

Also from

Abhishek, Kumar

View All

Also in

General Computers

View All