Several popular Python libraries support machine learning:
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scikit-learn: a widely used ML toolkit with clear examples and documentation..
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SciPy: useful for optimisation, statistics and scientific computing. Also includes support for sparse matrices.
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NumPy: provides fast multi-dimensional arrays, commonly used as input to ML algorithms.
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Pandas: offers DataFrames for working with structured data. Great for cleaning, filtering and analysis.
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Matplotlib: a plotting library used to create charts such as histograms, bar charts and scatter plots.
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Seaborn: built on top of matplotlib, offering attractive statistical graphics.
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Graphviz: a tool for visualising graphs and structures like decision trees.