This document outlines an online machine learning training that will cover classification and clustering techniques. It will introduce machine learning fundamentals and common Python libraries. Learners will work with sample datasets to practice preprocessing data, choosing features and labels, and using classifiers and clustering algorithms like K-means. Examples of classification models include eigenfaces and support vector machines, while iris data will be used for clustering demos.

1. Day-5
Machine Learning
(Classification & Clustering)
Two Weeks online
Live Industrial Training
ON
HANDS ON: MACHINE LEARNING
Day-11
THE NATIONAL SMALL INDUSTRIES CORPORATION In Association with
(A Government of India Enterprise)
. Kamalanagar, Kushaiguda, Hyderabad-500062
Date & Time
4-09-2020
2.30pm-3.30pm

2. Day-5
Content
• Classification
• Example
• Clustering
• Example

3. Day-5
USECASE
• Load dataset
• Pre-processing
• Choose features and labels
• Choose classifier
• Fit features, labels into classifier
• Predict

4. Day-5
Classification
• Eigen faces
• Support vector Machine

5. Day-5
Classification

6. Day-5
Clustering
• Iris
• K-Means
• 3D

7. Day-5
Clustering

8. Day-5
SUMMARY
• Classification
• Clustering

9. Day-5
Overall Summary
• Introduction to ML
• Types of Data
• Data sets
• Fundamentals of Python
• Machine Learning Libraries
• Classification
• Clustering

10. Day-5
Credits
• Harmonizer
• NSIC
• Google

11. Day-5

12. Day-5