Feature Selection for Machine Learning

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MP4 | Video: AVC 1280x720 | Audio: AAC 48KHz 2ch | Duration: 23 Hours | Lec: 143 | 396 MB | Language: English | Sub: English

Understand different methods of feature selection From beginner to advanced

What you'll learn
Understand different methods of feature selection
Implement different methods of feature selection
Reduce feature space in a dataset
Build simpler, faster and more reliable machine learning models
Analyse and understand the selected features

Requirements
A Python installation
Jupyter notebook installation
Python coding skills
Some experience with Numpy and Pandas
Familiarity with Machine Learning algorithms
Familiarity with scikit-learn

Description
Learn how to select features and build simpler, faster and more reliable machine learning models.

This is the most comprehensive, yet easy to follow, course for feature selection available online. Throughout this course you will learn a variety of techniques used worldwide for variable selection, gathered from data competition websites and white papers, blogs and forums, and from the instructor's experience as a Data Scientist.

You will have at your fingertips, altogether in one place, multiple methods that you can apply to select features from your data set.

The course starts describing simple and fast methods to quickly screen the data set and remove redundant and irrelevant features. Then it describes more complex techniques that select variables taking into account variable interaction, the feature importance and its interaction with the machine learning algorithm. Finally, it describes specific techniques used in data competitions and the industry.

The lectures include an explanation of the feature selection technique, the rationale to use it, and the advantages and limitations of the procedure. It also includes full code that you can take home and apply to your own data sets.

This course is therefore suitable for complete beginners in data science looking to learn how to go about to select features from a data set, as well as for intermediate and even advanced data scientists seeking to level up their skills.

With more than 50 lectures and 8 hours of video this comprehensive course covers every aspect of variable selection. Throughout the course you will use python as your main language.

Who this course is for?
Beginner Data Scientists who want to understand how to select variables for machine learning
Intermediate Data Scientists who want to level up their experience in feature selection for machine learning
Advanced Data Scientists who want to discover alternative methods for feature selection
Software engineers and academics switching careers into data science
Software engineers and academics stepping into data science
Data analysts who want to level up their skills in data science
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