Machine Learning

⌘Ctrlk

Machine Learning

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 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?

Powered by GitBook

On this page

Learning
evaluation metrics
Model Validation

test

PreviousModel Validation NextThe bias, variance, and regularization properties

Last updated 6 years ago