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Artificial intelligence
Unit 1
How AI Works
Introduction to AI
Machine Learning and AI
Natural Language Processing (NLP)
Computer Vision and AI
AI Ethics and Bias
Unit 2
What is NLP
Introduction to NLP
NLP Techniques
NLP in AI Applications
Unit 3
Basic AI projects for Resume
Introduction to Basic AI Projects for Resume
Implementing a Simple AI Project
Showcasing AI Projects on a Resume
Unit 4
When is AGI coming?
Current State of AGI Research
Predictions and Timelines for AGI
Technological Milestones and AGI Development
Challenges and Risks of AGI
Pathways to AGI
Unit 1 • Chapter 2
Machine Learning and AI
Summary
False
Concept Check
What is an important aspect of Machine Learning?
Algorithm complexity
Feature engineering
Model accuracy
Data preparation
Which technique is commonly used in AI for decision-making?
Deep Learning
Unsupervised Learning
Supervised Learning
Reinforcement Learning
What can help improve a Machine Learning model's performance?
Hyperparameter tuning
Adding noise to data
Ignoring missing values
Applying feature scaling
What is a key challenge in implementing AI systems?
Ethical considerations
Hardware limitations
Lack of talent in the field
Data storage costs
Which type of learning requires labeled training data?
Unsupervised Learning
Semi-supervised Learning
Supervised Learning
Reinforcement Learning
Check Answer
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Introduction to AI
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Natural Language Processing (NLP)