fast track machine learning part 1 (machine learning overview) - types of machine learning problems

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Inspire…Educate…Transform. The best place for students to learn Applied Engineering http://www.insofe.edu.in Dr. K. V Dakshinamurthy Part 1 (Machine Learning Overview) - Types of Machine Learning Problems President, INSOFE

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In part 1 of Fast track Machine learning (Machine Learning Overview) series Dr. Dakshinamurthy Kolluru gives a thousand feet view of Machine Learning. One can divide the problems in Machine Learning as Classification, Regression and Optimization. Where in Classification can be defined as splitting the space. Regression is fitting a curve and regression can also be set up as a classification problem. Optimization is on a curve, find the maximum and minimum points.

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Page 1: Fast Track Machine Learning Part 1 (Machine Learning Overview) - Types of Machine Learning Problems

Inspire…Educate…Transform.

The best place for students to learn Applied Engineering http://www.insofe.edu.in

Dr. K. V Dakshinamurthy

Part 1 (Machine Learning

Overview) - Types of

Machine Learning Problems

President, INSOFE

Page 2: Fast Track Machine Learning Part 1 (Machine Learning Overview) - Types of Machine Learning Problems

The best place for students to learn Applied Engineering 2 http://www.insofe.edu.in

Page 3: Fast Track Machine Learning Part 1 (Machine Learning Overview) - Types of Machine Learning Problems

The best place for students to learn Applied Engineering 3 http://www.insofe.edu.in

Classification; Supervised and Unsupervised

Page 4: Fast Track Machine Learning Part 1 (Machine Learning Overview) - Types of Machine Learning Problems

The best place for students to learn Applied Engineering 4 http://www.insofe.edu.in

Classification is a pattern search

Page 5: Fast Track Machine Learning Part 1 (Machine Learning Overview) - Types of Machine Learning Problems

The best place for students to learn Applied Engineering 5 http://www.insofe.edu.in

Classification is a pattern search

Page 6: Fast Track Machine Learning Part 1 (Machine Learning Overview) - Types of Machine Learning Problems

The best place for students to learn Applied Engineering 6 http://www.insofe.edu.in

Forecast

Yield (profit/acre) of a seed as a function of altitude

Page 7: Fast Track Machine Learning Part 1 (Machine Learning Overview) - Types of Machine Learning Problems

The best place for students to learn Applied Engineering 7 http://www.insofe.edu.in

Prediction and forecasting

Page 8: Fast Track Machine Learning Part 1 (Machine Learning Overview) - Types of Machine Learning Problems

The best place for students to learn Applied Engineering 8 http://www.insofe.edu.in

Can we convert it into a search problem?

• Bin the variable we are predicting into

low, medium, high

– As number of bins increase, accuracy

increases but understanding reduces

Page 9: Fast Track Machine Learning Part 1 (Machine Learning Overview) - Types of Machine Learning Problems

The best place for students to learn Applied Engineering 9 http://www.insofe.edu.in

Optimization

Page 10: Fast Track Machine Learning Part 1 (Machine Learning Overview) - Types of Machine Learning Problems

The best place for students to learn Applied Engineering 10 http://www.insofe.edu.in

Optimization as pattern search

• Some combinations give optimum

outputs and some don’t

• So, optimization is also a Boolean

search

Page 11: Fast Track Machine Learning Part 1 (Machine Learning Overview) - Types of Machine Learning Problems

The best place for students to learn Applied Engineering 11 http://www.insofe.edu.in

YouTube link

• For a detailed video on this topic visit

the following link:

http://www.youtube.com/watch?v=4Dp

6p9ZuoO8

Page 12: Fast Track Machine Learning Part 1 (Machine Learning Overview) - Types of Machine Learning Problems

The best place for students to learn Applied Engineering 12 http://www.insofe.edu.in

International School of Engineering

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school-of-engineering

This presentation may contain references to findings of various reports available in the public domain. INSOFE makes no representation as to their accuracy or that the organization

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