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Data Science & Analytics

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Training Data for ML: From Annotation to Data Science (2023)
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ML for Network Traffic & Video Quality: JavaScript Apps (2024)
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ML-Aided Analysis & Additive Manufacturing of Composite Structures (2025)
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ML & SQL Made Simple: Practical Data Science Guide (2024)
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ML for Physical Sciences: Fundamentals & Julia Prototyping (2023)
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ML for Business Analytics: Concepts & Applications in R (2023)
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Python Data Mining: Quick Guide for Beginners (2023)
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Big Data, ML & Applications: BigDML 2021 Conference Proceedings
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Probabilistic ML for Finance: Generative AI with Python (2023)
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Data Mining: Concepts, Techniques & Applications (2022)
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Numerical Machine Learning: Theoretical & Practical Approaches (2023)
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Graph-Powered Analytics & ML with TigerGraph: Business Insights (2023)
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Data Mining & ML Applications: Insights for Data-Driven Decisions (2022)
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Machine Learning in Financial Analytics: Approaches & Strategies
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Probability & Statistics for Machine Learning: A Practical Textbook (2024)
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Statistical ML for Engineering: Applications & Methods (2024)
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Machine Learning on Geographical Data: Python Applications & Use Cases
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Machine Learning Production Systems: Engineering Models & Pipelines
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Machine Learning for Engineers: Practical Approaches (2023)
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Social Media Data Mining & Analytics: AI Insights
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MATLAB ML Recipes: Problem-Solution Approach (2024)
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Intro to ML & Security: Python & Cloud-Based AI (2024)
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Practical ML with R: Tutorials & Case Studies (2024)
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Learn Data Mining with Excel: ML Step-by-Step Guide (2023)
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Data Mining & Big Data: DMBD 2023 Conference Insights
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Data-Driven Farming: AI & ML in Agriculture (2024)
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ML with Qlik Sense: AI-Powered Data Insights (2023)
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Quantum ML: A Modern Approach to AI & Computing (2024)
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