This document discusses the development of a machine learning model called Learnware that aims to help students succeed in online learning. It analyzes student data to identify those needing assistance, with an accuracy of over 70%. The team plans to improve the model's accuracy to 85-90% and integrate it into existing learning platforms via a web library. Their goal is to build learning environments that help students become professionals by addressing issues like high failure rates in online learning.

1. learnware
helping students achieve success
https://github.com/kurosouza/learnware

2. Our goal: building
learning environments
that help students
become professionals

3. The perils of online learning

Online learning resources have
become vast and overwhelming

High failure rate among online
learners

Students tend to under-estimate the
effort needed for online learning
44%44% 56%

4. A machine learning model
that helps you identify
students that need
assistance.
Powered by IBM DB2

5. Built on cutting-edge cloud technology
Leveraging high
quality data
Built using records from
over 30 000 students
Integrating the
stability of the IBM
DB2 database
Our model achieves
over 70% accuracy
The IBM DB2 database
allows us to easily build our
model in the cloud
We can easily iterate
and improve the
performance of our
model

6. The team
We build cloud applications!
Kuro Souza Alter Ego Guy
Software Engineer, ML
Enthusiast
Genius, Trouble maker

7. Roadmap
Building version
0.1 ML model
Working version of ML
model
Improve model
accuracy
Get model performance
up to 85-90 %
Build web integration
library
Build a web library to allow users
add learnware to their exising
learning platforms
Release alpha
version
Release an alpha version that
people can try
Oct Nov Jan Feb

8. Our project on github:
http://github.com/kurosouza/learnware