Course Outline
Getting Started
- Quick Intro
- Installation Guide
- Downloading Template
- Deploying an Engine
- Customizing an Engine
- App Integration Overview
Developing PredictionIO
- System Architecture
- Event Server Overview
- Collecting Data
- Learning DASE
- Implementing DASE
- Evaluation Overview
- Intellij IDEA Guide
- Scala API
Machine Learning Education and Usage Examples
- Comics Recommendation
- Text Classification
- Community Contributed Demo
- Dimensionality Reducation and usage
PredictionIO SDKs (Select One)
- Java
- PHP
- Python
- Ruby
- Community Contributed
Requirements
Programming knowledge of one of the following:
- Java
- Ruby
- PHP
- Python
- Swift
- Node JS
- C#/.Net
- Lavarel Wrapper
Testimonials (4)
Keeping it short and simple. Creating intuition and visual models around the concepts (decision tree graph, linear equations, calculating y_pred manually to prove how the model works).
Nicolae - DB Global Technology
Course - Machine Learning
The details and the presentation style.
Cristian Mititean - Accenture Industrial SS
Course - Azure Machine Learning (AML)
Working from first principles in a focused way, and moving to applying case studies within the same day
Maggie Webb - Department of Jobs, Regions, and Precincts
Course - Artificial Neural Networks, Machine Learning, Deep Thinking
That it was applying real company data. Trainer had a very good approach by making trainees participate and compete