I. Artificial Intelligence (AI)
Artificial Intelligence is the branch of computer science that enables machines to think, learn, and make decisions like humans.
II. Goal of Artificial Intelligence
The main goal of AI is to create systems that can perform tasks requiring human intelligence such as learning, reasoning, and problem-solving.
III. Components of Natural Intelligence
Natural intelligence includes learning, reasoning, perception, problem-solving, and language understanding.
IV. Natural Language Processing (NLP)
Natural Language Processing is a field of AI that helps computers understand, interpret, and respond to human language.
V. Computer Vision
Computer Vision is the ability of machines to see and interpret images or videos.
Example: Face recognition in smartphones.
VI. Machine Learning (ML)
Machine Learning is a subset of AI that allows systems to learn from data without explicit programming.
Steps: Data collection → Data preprocessing → Model training → Testing → Prediction.
VII. Deep Learning
Deep Learning is a type of machine learning that uses neural networks with multiple layers.
Steps: Data collection → Neural network design → Training → Validation → Output prediction.
VIII. Relationship between AI, ML, and Deep Learning
AI is the broad field, ML is a subset of AI, and Deep Learning is a subset of ML.
IX. Supervised vs Unsupervised Learning:
Supervised learning: Uses labeled data (e.g., classification).
Unsupervised learning: Uses unlabeled data (e.g., clustering).
Difference: Presence of labeled data.
X. Two Use Cases of NLP
1. Chatbots
2. Language translation
XI. Sentiment Analysis
Sentiment analysis is an NLP technique used to identify emotions or opinions (positive, negative, neutral) from text such as reviews, tweets, or feedback.
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