Udemy – Feature Engineering for Machine Learning 2024-9
Udemy – Feature Engineering for Machine Learning 2024-9 Downloadly IRSpace

Feature Engineering for Machine Learning is a tutorial from Udemy site that introduces you to feature engineering in machine learning and teaches you how to convert variables into data and build better models. If you’ve ever taken your first steps in data science and become familiar with prior models, you’re likely to face more difficult challenges. At this point you may notice that your code looks cluttered and many values are vague.
This course is a comprehensive course in feature engineering and variables for machine learning that teaches you many engineering techniques. In this course you will learn how to identify missing data, encoding definitive variables, converting numeric variables, deleting segments, managing time and date variables, working with different time zones, and managing composite variables and various application projects You solve it.
Courses taught in this course:
- Learn different techniques to show missing data
- Convert deterministic variables to numbers
- Working with rare and unseen categories
- Convert diagonal variables to Gaussian
- Converting Numeric Variables to Discrete
Feature Engineering for Machine Learning course specifications:
- English language
- Publisher: Udemy
- Duration: 13h 24m
- Number of lessons: 202
- Level of education: Intermediate
- Instructor: Soledad Galli
- File format: mp4
Course headings
Course prerequisites
- A Python installation
- Jupyter notebook installation
- Python coding skills
- Some experience with Numpy and Pandas
- Familiarity with Machine Learning algorithms
- Familiarity with Scikit-Learn
Pictures
Sample movie
Installation guide
View with your favorite Player after Extract.
English subtitle
Quality: 720p
Changes:
Version 2022/3 has increased by 15 lessons and 41 minutes compared to 2019/3.
Version 2023/4 compared to 2022/3 has increased the number of 75 lessons and the duration of 3 hours and 30 minutes.
The 2024/9 version has a reduction of 11 lessons and a duration of 34 minutes compared to 2023/4. The course quality has also been increased from 720p to 1080p.
Download link
Size
5.4 GB