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Time Series Analysis
Pattern Recognition Chronicles
Learning Outcome
5
Analyze future challenges in AI systems
4
Connect pattern recognition with AI & real-world use
3
Explore major theories (Template, Prototype, Feature-based)
2
Identify how humans recognize patterns
1
Understand what pattern recognition is
Recall
"Think Before We Start"
How do you recognize a face instantly?
How do you identify spam messages?
How do you predict exam questions?
Analogy
“Your Brain is a Prediction Machine”
Human recognizing face
AI detecting object
“Your Brain is a Prediction Machine”
You see a face in 0.5 seconds.
AI scans 1000s of images to do the same.
Human recognizing face
AI detecting object
When you meet a friend in crowd -- No thinking, instant recognition.
Transition to Technical Concept
So What Is Pattern Recognition?
Input Brain Memory Decision
Pattern Recognition = Matching new information with stored memory
Introduction to Pattern Recognition
Definition:
Pattern Recognition means finding patterns or trends in data automatically using algorithms.
It helps machines understand data in areas like AI, images, speech, and time series.
Why Pattern Recognition Matters
- Automates decision making
- Enables predictive analytics
- Used in classification & clustering
- Helps detect anomalies
Key Components (Overview)
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Data Acquisition
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Preprocessing
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Feature Extraction
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Classification
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Post-processing
Components Explained
Sensor: collects raw data
Preprocessing: removes noise
Feature Extraction: selects important info
Classification: makes decision
Post-processing: improves result
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Supervised → labeled data
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Unsupervised → no labels
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Semi-supervised → mixed data
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Reinforcement → reward-based learning
Types of Pattern Recognition
Learning Types Explained
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Supervised Learning
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Unsupervised Learning
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Semi-supervised Learning
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Reinforcement Learning
Feature Extraction (Core Concept)
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Extract meaningful information from data
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Helps distinguish patterns
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Examples:
1.Image: edges, colors
2.Text: word frequency
3.Audio: pitch
4.Time series: mean, variance
Classification Algorithms
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Logistic Regression
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k-NN
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SVM
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Decision Trees
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Naive Bayes
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Neural Networks
Pattern Recognition in Time Series
- Shape-based matching
- Feature-based modeling
- Deep learning (RNN, LSTM)
Use case: stock price prediction
Quiz
Which platform is mainly used for professional networking and B2B marketing ?
A. Facebook
B. Instagram
C. LinkedIn
D. Snapchat
Quiz-Answer
Which platform is mainly used for professional networking and B2B marketing ?
A. Facebook
B. Instagram
C. LinkedIn
D. Snapchat
Artificial Intelligence-Pattern Recognition Chronicles
By Content ITV
