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Syllabus
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Syllabus
LECTURE NOTES
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UNIT 1
1.1 INTRODUCTION
1.2 WORKING OF AI
1.3 TYPES OF AI
1.4 FOUNDATIONS OF AI
1.5 MACHINE LEARNING
1.6 Computer Vision
1.7 NLP
UNIT II
2.1 COMPONENTS OF ML
2.2 TYPES OF ML
2.3 Traditional Vs Machine Learning Approach
2.4 APPLICATIONS OF ML
2.5 SUPERVISED LEARNING
2.6 UNSUPERVISED LEARNING
UNIT III
3.1 SUPPORT VECTOR MACHINE
3.2 REGRESSION
3.3 RANDOM FOREST
3.4 ARTIFICIAL NEURAL NETWORK
3.5 KNN
3.6 CLUSTERING
UNIT 4
4.1 REINFORCEMENT LEARNING
4.2 SARSA
4.3 Q LEARNING
4.4 DEEP LEARNING
4.5 AI Vs ML Vs DL
4.6 APPLICATION OF DL
UNIT 5
5.1 APPLICATION OF AI IN STRUCTURAL ENGINEERING
5.2 APPLICATIONS OF AI IN CONCRETE TECHNOLOGY
5.3 APPLICATIONS OF AI IN CONSTRUCTION MANAGEMENT
5.4 APPLICATION OF AI IN TRANSPORTATION
5.5 APPLICATION OF AI IN SURVEYING
5.6 APPLICATION OF AI IN DISASTER MANAGEMENT
QUESTION BANK
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UNIT I
UNIT II
UNIT III
UNIT IV
UNIT V
PUZZLE
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UNIT I
UNIT II
UNIT III
UNIT IV
UNIT V
23CEE305 – Introduction to AI and Machine Learning
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