Build Machine Learning Projects

Build Machine Learning Projects

Not currently available

Available on Nov. 29, 2019, 9:50 a.m. PST.

About this Course

Artificial Intelligence (AI) and Machine Learning (ML) have become increasingly necessary to translate today’s data into direct business value. This course introduces learners to the most important aspects of putting together a machine learning project plan. Only an estimated 20% of ML projects ever make it into production, so it is crucial for businesses to understand how to prepare, plan, and execute on a well-defined, action-oriented strategy.

This course presents a repeatable process of six steps that can be followed for any machine learning workflow, and shows how companies are implementing ML with MapR to maximize their business results.

This is the second course in the Machine Learning Business Series.

What's Covered

Course Lessons Lab Activities

1: Prepare Your Project

Overview of Artificial Intelligence and Machine Learning
Step 1: Identify Business Need and Plan
Step 2: Data Management
Step 3: Feature Selection and Engineering

No labs

2: Implement to Production

Step 4: Algorithm and Framework Selection
Step 5: Model Training and Validation
Step 6: Implementation to Production and Monitoring
How MapR Can Help

No labs

Prerequisites

  • Completion of Introduction to Artificial Intelligence and Machine Learning

Curriculum

  • Prepare Your Project
  • Quiz 1
  • Implement to Production
  • Quiz 2
  • Course Materials
  • Slide Guide (Transcript)

About this Course

Artificial Intelligence (AI) and Machine Learning (ML) have become increasingly necessary to translate today’s data into direct business value. This course introduces learners to the most important aspects of putting together a machine learning project plan. Only an estimated 20% of ML projects ever make it into production, so it is crucial for businesses to understand how to prepare, plan, and execute on a well-defined, action-oriented strategy.

This course presents a repeatable process of six steps that can be followed for any machine learning workflow, and shows how companies are implementing ML with MapR to maximize their business results.

This is the second course in the Machine Learning Business Series.

What's Covered

Course Lessons Lab Activities

1: Prepare Your Project

Overview of Artificial Intelligence and Machine Learning
Step 1: Identify Business Need and Plan
Step 2: Data Management
Step 3: Feature Selection and Engineering

No labs

2: Implement to Production

Step 4: Algorithm and Framework Selection
Step 5: Model Training and Validation
Step 6: Implementation to Production and Monitoring
How MapR Can Help

No labs

Prerequisites

  • Completion of Introduction to Artificial Intelligence and Machine Learning

Curriculum

  • Prepare Your Project
  • Quiz 1
  • Implement to Production
  • Quiz 2
  • Course Materials
  • Slide Guide (Transcript)