Udemy – Machine Learning with Imbalanced Data 2024-9

Description

Machine Learning with Imbalanced Data is a training course on unbalanced data tackle techniques and improving the efficiency of your machine learning model. If you are currently working on unbalanced datasets and want to improve the performance of your model or you want to learn techniques to help you deal with data imbalances, then this course is for you. We teach you everything you need to work with unbalanced datasets step by step with fun instructional videos. During this comprehensive course, we will teach all the available methodologies for working with unbalanced datasets and discuss the logic of how they work, how to use them in Python, and their advantages and disadvantages.

What you will learn in the Machine Learning with Imbalanced Data course:

• Randomly under-sampling methods
• “Low sampling” methods that focus on observations that are difficult to classify.
• Low sampling methods to increase the number of minority observations
• Ways to Build Dummy Data to Increase Minority Class Examples
• SMOTE and its variables
• Use of group methods with sampling techniques to improve model efficiency
• The best evaluation criteria for use in unbalanced datasets

Course specifications

Publisher: Udemy
Instructors: Soledad Galli
Language: English
Level: Average
Lessons: 106
Duration: 9 hours and 15 minutes

Course Content

Course prerequisites:

Pictures

Sample film

Installation guide

After Extract, watch with your favorite Player.

English subtitle

Quality: 720

Changes:

Version 2022/3 compared to 2021/1 has increased the number of 25 lessons and the duration of 2 hours and 57 minutes.

Version 2024/9 compared to 2022/3 has decreased the number of 23 lessons and the duration of 2 hours and 10 minutes.

Download link

Download Part 1 – 1 GB

Download Part 2 – 1 GB

Download Part 3 – 539 MB

File password (s): www.downloadly.ir

Size

2.53 GB