Mathematics
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Data Science Fundamentals With R, Python, and Open Data
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Advancing Edge Artificial Intelligence: System Contexts
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Data Science Fundamentals With R, Python, and Open Data
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Graph Algorithms for Data Science: With Examples in Neo4j
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Data Science and Machine Learning for Non-Programmers: Using SAS Enterprise Miner
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Foundations of Data Science With Python
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Models for Multi-State Survival Data: Rates, Risks, and Pseudo-Values
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Perspectives on Ethical Hacking and Penetration Testing
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Cybersecurity Management: An Organizational and Strategic Approach
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Models for Multi-State Survival Data: Rates, Risks, and Pseudo-Values
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Graph Algorithms for Data Science with Neo4j Examples
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Data Science Fundamentals with R, Python, and Open Data: A Practical Approach
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Cybersecurity Management: An Organizational and Strategic Approach
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Math 0-1 – Matrix Calculus in Data Science and Machine Learning
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Mathematics of ML: Supervised Learning & Beyond (2024)
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Exercises in Applied Math: Info Theory, ML & Wavelets (2024)
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Mathematics for ML in Python: Theory & Applications (2024)
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Mathematical Analysis of ML Algorithms: AI Theory & Proofs (2023)
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Kernel Methods for ML: 100 Math & Python Exercises (2022)
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Before Machine Learning Vol. 1: Linear Algebra for AI (2023)
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Mathematics & Computer Science, Volume 1: Advanced Computational Concepts (Scrivener Publishing, 2024)
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Mathematical Engineering of Deep Learning: AI & Computational Intelligence (CRC Press, 2024)
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Mathematics & Computer Science, Volume 2 (Scrivener Publishing, 2024)
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Many-Sorted Algebras for Deep Learning & Quantum Technology (Morgan Kaufmann Elsevier, 2024)
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Mathematics of Deep Learning: A Beginner’s Guide (De Gruyter, 2023)
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Deep Learning Through the Prism of Tensors: A New Perspective (2024)
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Mathematics for Machine Learning: Master Algorithms & Concepts
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