Machine Learning

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Introduction
Self LEarning
Why Statstics in ML Or Data Science
How important is interpretability for a model in Machine Learning?
What are the most important machine learning techniques to master at this time?
Learning
Steps in machine learning model development and deployment
Statistical fundamentals and terminology
Statistics
Spark MLib
Terminology
Machine Learning Steps
Preprocessing and Feature selection techniues
The importance of variables feature selection/attribute selection
- Feature Selection
Feature engineering
Hyperplanes
cross-validation
Machine learning losses
When to stop tuning machine learning models
Train, validation, and test data
input data structure
Why are matrices/vectors used in machine learning/data analysis?
OverView
Data scaling and normalization
Questions
Which machine learning algorithm should I use?

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The importance of variables feature selection/attribute selection
Feature Selection

The key metrics to focus on

The key metrics to focus

Previousbackward selection or backward elimination NextFeature engineering

Last updated 6 years ago

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