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

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