wehub-resource-sync
18 lines
794 B
TeX
18 lines
794 B
TeX
Building intelligent machines to transform data into knowledge
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The three different types of machine learning
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Making predictions about the future with supervised learning
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Classification for predicting class labels
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Regression for predicting continuous outcomes
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Solving interactive problems with reinforcement learning
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Discovering hidden structures with unsupervised learning
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Finding subgroups with clustering
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Dimensionality reduction for data compression
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An introduction to the basic terminology and notations
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A roadmap for building machine learning systems
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Preprocessing – getting data into shape
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Training and selecting a predictive model
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Evaluating models and predicting unseen data instances
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Using Python for machine learning
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Installing Python packages
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Summary
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