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start learning
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Training a model on labeled data to make predictions
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start learning
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Training a model on unlabeled data to discover patterns
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start learning
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Training a model to take actions for maximum reward
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Supervised vs Unsupervised Learning unsupervised uses unlabeled data start learning
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Supervised uses labeled data
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Supervised vs Reinforcement Learning reinforcement uses trial and error start learning
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Supervised uses labeled data
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Unsupervised vs Reinforcement Learning reinforcement uses trial and error start learning
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Unsupervised uses unlabeled data
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Types of Machine Learning start learning
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start learning
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Correct output for a given input in machine learning
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Model Performance Evaluation start learning
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Comparing predictions to ground truth
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Supervised Learning Applications natural language processing start learning
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Unsupervised Learning Applications start learning
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Reinforcement Learning Applications start learning
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unsupervised has unlabeled data start learning
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Supervised has labeled data reinforcement has no specific guidance
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Labeled Data Requirements start learning
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Supervised requires labeled data
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Unsupervised Learning Limitations may require human guidance start learning
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May not discover all patterns
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Reinforcement Learning Limitations may not be practical for all tasks start learning
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May require a lot of trial and error
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Machine Learning Suitability start learning
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Depends on problem and data available
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start learning
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Categorical or numerical output may affect choice of approach
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start learning
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Structured or unstructured data may affect choice of approach
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Labeled Data Requirements start learning
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Supervised requires labeled data
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start learning
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Having a clear objective may affect choice of approach
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start learning
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Amount of required supervision may affect choice of approach
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Model Provided with Correct Output start learning
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Model Not Provided with Specific Instructions start learning
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Model Learns through Trial and Error start learning
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start learning
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Make predictions based on labeled data
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Unsupervised Learning Goal start learning
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Discover patterns in unlabeled data
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Reinforcement Learning Goal start learning
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Maximize reward through trial and error
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Machine Learning to Group Similar Data start learning
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Machine Learning to Optimize Performance Over Time start learning
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