Machine Learning is the study of algorithms that learn from the data. OCR is one of its application.

1. Machine Learning
(OCR)
Presented By-
Raunaq Kataria
Amit Gupta
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2. Overview
1. What is it ?
2. What are the Applications ?
3. What are the types of ML Algorithms ?
4. Why Machine Learning ?
5. What is our Aim ?
6. OCR
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3. What is Machine Learning ?
• Study of Algorithms that can ‘learn from data’
through iterations (experience)
• Without being ‘explicitly programmed’
• Operation:
1. Build models on Inputs.
2. Making Predictions
3. E.g. Predicting Flight Delays
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4. Applications
• Spam mail (recognition)
• Web click data (recommendations)
• Security (Pattern recognition, face detection)
• Business (Stocks, user behaviors)
• Medical (Research on medical records)
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5. Types Of Algorithms
• There are mainly 2 types of ML Algorithms:
1. Supervised
2. Unsupervised
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6. Why Machine Learning?
• Beginning towards the aim of Ultimate A.I.
i.e.
1. Self Aware
2. Fully Conscious
3. As Intelligent as The Human Race.
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7. Our Aim
• Implementing Machine Learning Algorithms to
execute :
OCR : Optical Character Recognition
using Supervised Machine Learning Algorithm
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8. What is OCR ?
• OCR :
1. First step in the field of Computer Vision
2. A part of AI
• Conversion of images of Handwritten or printed text into
machine encoded text
• Implement on MATLAB through supervised learning
algorithm
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9. INPUT
TYPEWRITTEN TEXT
IMAGE
OUTPUT
MACHINE
ENCODED TEXT
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10. Preprocessing
• converted
Pixel Intensities
(in Matrix Forms)
into two matrices
Large no of
training examples
(say: 5000)
X : rows = no. of training examples
columns = pixel intensities
Y : rows = no. of labels under which
the training examples are classified
Training Data
Set
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11. TRAINING
DATA SET
Output
LEARNING ALGO
(logistic regression)
Hypothesis
Function (h)
Input Data Set
<
Partial Output
‘n’ iterations

12. OCR - PROSPECTS
• Extract key info from business documents,
e.g. insurance policy, passport, bank statement etc.
• Automatic number plate recognition
• Assistive technology for visually impaired users
( text-to-speech converter)
• Extracting business card info into a contact list
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13. BIBLIOGRAPHY
• Lectures by - (Andrew Ng, Machine Learning-
Stanford University )
• http://en.wikipedia.org/wiki/Machine_learning
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14. Thank You
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