Artificial Intelligence Foundations: Machine Learning

Offered By: LinkedIn Learning

Tags

Machine Learning Courses Supervised Learning Courses Unsupervised Learning Courses Reinforcement Learning Courses Semi-supervised Learning Courses Decision Trees Courses K-Nearest Neighbors Courses

Course Description

Overview

Learn about the machine learning lifecycle and the steps required to build systems in this hands-on course.

Syllabus

Introduction

Introduction to AI foundations: Machine learning course
Reviewing the course scenarios

1. Understanding Machine Learning

Exploring machine learning
Examining how machines learn

2. Implementing a Machine Learning Solution

Breaking down the machine learning lifecycle
Framing machine learning problems
Identifying a pre-built model
Understanding tools used to train a model

3. Preparing Data for Machine Learning

Obtaining data
Visualizing and understanding data
Understanding feature engineering
Demo: Performing feature engineering

4. Training a Machine Learning Model

Understanding learning algorithms and model training
Exploring learning algorithms for classification
Reviewing learning algorithms for regression
Examining additional learning algorithms
Training a custom machine learning model
Demo: Training a custom machine learning model

5. Evaluating Model Performance

Exploring common classification metrics
Understanding the confusion matrix
Exploring common regression metrics
Determining feature importance
Combating bias

6. Operationalizing a Machine Learning Pipeline

Structuring a machine learning pipeline
Demo: Designing and building a pipeline

Conclusion

Your machine learning journey

Taught by

Doug Rose

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