Description
Feature Engineering for Machine Learning is a tutorial from the Udemy website that introduces you to feature engineering in machine learning and shows you how to transform variables into data and build better models. If you’ve already taken your first steps in data science and become familiar with previous models, you’re probably facing greater challenges. At this point, you may notice that your code looks messy and many values are vague.
This course is a comprehensive course on feature engineering and variables for machine learning that will teach you many engineering techniques. In this course, you will learn how to identify missing data, encode definitive variables, convert numeric variables, delete segments, manage time and date variables, work with different time zones, and manage compound variables and different application projects. You solve it.
Courses taught in this course:
- Learn different techniques to display missing data
- Convert deterministic variables to numbers
- Working with rare and invisible categories
- Convert diagonal variables to Gaussian variables
- Convert numeric variables to discrete ones
Specifications of the Feature Engineering for Machine Learning course:
- English language
- Duration: 13h 58m
- Number of teaching hours: 213
- Education level: Intermediate
- Instructor: Soledad Galli
- File format: mp4
Course headings on 2023/5
Course requirements
- A Python installation
- Installing the Jupyter notebook
- Python coding skills
- Some experience with Numpy and Pandas
- Familiarity with machine learning algorithms
- Familiarity with Scikit-Learn
Pictures
Sample film
installation Guide
After extracting, watch with your favorite player.
English subtitles
Quality: 720p
Changes:
The 2022/3 version has increased by 15 lessons and 41 minutes compared to 2019/3.
In version 2023/4, compared to 2022/3, the number was increased to 75 lessons and the duration to 3 hours and 30 minutes.
Download link
File password(s): free download software
Size
3.96GB