You cannot select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
23 lines
1.8 KiB
Markdown
23 lines
1.8 KiB
Markdown
---
|
|
title: "OpenPOWER and AI Workshop at IIT Delhi Campus"
|
|
date: "2018-11-13"
|
|
categories:
|
|
- "blogs"
|
|
tags:
|
|
- "featured"
|
|
---
|
|
|
|
Josiah Samuel, advisory software engineer, IBM
|
|
|
|
[](http://opf.tjn.chef2.causewaynow.com/wp-content/uploads/2018/11/IIT-Delhi.jpg)
|
|
|
|
I recently attended the OpenPOWER and AI Workshop at the Indian Institute of Technology Delhi. This workshop gathered 30 students to learn about IBM and its work with Artificial Intelligence.
|
|
|
|
I was able to offer these students hands-on sessions discussing PowerAI, SnapMl and Machine Learning. One portion of the workshop focused on walking through a problem statement. This workshop's statement was: "How to make a quick prediction whether a credit amount can be sanctioned or not." After explaining the assignment, the students were taught how to do explanatory data analysis using the Matplotlib library. These charts showed the co-relation between various attributes. Students were taught how to convert raw data into a format machine learning algorithms can understand. All along, the students were allowed to try on their own based on the provided Power8 setup.
|
|
|
|
Other tools that were used to solve this problem included the Scikit-learn's logistic Regression API to train the model, using a small dataset which shows low accuracy. This allowed the students to view the metrics. Students learned that the more the dataset was increased, the more accurate the data became.
|
|
|
|
Following this, we contrasted the Scikit-learn's to SnapML. SnapML can perform ML training on large datasets with at least a 10x decrease in training time compared to Scikit-learn's training time with no compromise on the model's Accuracy.
|
|
|
|
It was an incredible experience to share my work with the IIT Delhi students and walk them through a real-life scenario.
|