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Domanda Risposta
Supervised Learning
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Training a model on labeled data to make predictions
Unsupervised Learning
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Training a model on unlabeled data to discover patterns
Reinforcement Learning
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Training a model to take actions for maximum reward
Supervised vs Unsupervised Learning
unsupervised uses unlabeled data
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Supervised uses labeled data
Supervised vs Reinforcement Learning
reinforcement uses trial and error
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Supervised uses labeled data
Unsupervised vs Reinforcement Learning
reinforcement uses trial and error
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Unsupervised uses unlabeled data
Types of Machine Learning
unsupervised
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Supervised
reinforcement
"Ground Truth"
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Correct output for a given input in machine learning
Model Performance Evaluation
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Comparing predictions to ground truth
Supervised Learning Applications
natural language processing
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Image classification
Unsupervised Learning Applications
anomaly detection
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Clustering
Reinforcement Learning Applications
robot control
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Game playing
Input Data Structure
unsupervised has unlabeled data
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Supervised has labeled data
reinforcement has no specific guidance
Labeled Data Requirements
reinforcement does not
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Supervised requires labeled data
Unsupervised Learning Limitations
may require human guidance
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May not discover all patterns
Reinforcement Learning Limitations
may not be practical for all tasks
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May require a lot of trial and error
Machine Learning Suitability
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Depends on problem and data available
Output Type Impact
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Categorical or numerical output may affect choice of approach
Input Data Impact
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Structured or unstructured data may affect choice of approach
Labeled Data Requirements
unsupervised does not
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Supervised requires labeled data
Clear Objective Impact
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Having a clear objective may affect choice of approach
Human Supervision Impact
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Amount of required supervision may affect choice of approach
Model Provided with Correct Output
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Supervised learning
Model Not Provided with Specific Instructions
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Unsupervised learning
Model Learns through Trial and Error
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Reinforcement learning
Supervised Learning Goal
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Make predictions based on labeled data
Unsupervised Learning Goal
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Discover patterns in unlabeled data
Reinforcement Learning Goal
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Maximize reward through trial and error
Machine Learning to Group Similar Data
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Unsupervised learning
Machine Learning to Optimize Performance Over Time
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Reinforcement learning
Crea delle schede
hiszpański

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