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After AlphaGo famously outperformed the world’s top Go player, the power of machine learning became evident. This e‑book equips you with the knowledge and practical code to harness similar capabilities across any data domain.

Spanning 454 pages, the book covers:

• Foundational concepts of supervised, unsupervised, and reinforcement learning.
• Hands‑on tutorials on data preprocessing, feature engineering, and model selection.
• Strategies to tune hyperparameters and evaluate model performance.
• Techniques for deploying trained models as RESTful APIs or embedding them into web applications.

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Whether you’re a data scientist, developer, or curious learner, this resource will help you transform raw data into actionable insights using Python’s leading ML libraries.