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15 Math Concepts Every Data Scientist Should Know: Understand and learn how to apply the math behind data science algorithms
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A Handbook of Mathematical Models with Python: Elevate your machine learning projects with NetworkX, PuLP, and linalg
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Bayesian Analysis with Python – Third Edition: A practical guide to probabilistic modeling
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Data Visualization: A Successful Design Process
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Haskell Design Patterns
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Mathematics of Machine Learning: Master linear algebra, calculus, and probability for machine learning
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Principles of Data Science – Third Edition: A beginner’s guide to essential math and coding skills for data fluency and machine learning
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Python Deep Learning – Third Edition: Understand how deep neural networks work and apply them to real-world tasks
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Taking Tinkercad to the Next Level: Enhance your ability to design, model, and 3D print with one of the most intuitive CAD programs
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The Kaggle Book: Data analysis and machine learning for competitive data science
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