Data Science
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Privacy-Preserving ML: Secure & Ethical AI Pipelines (2024)
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ML Evaluation: Ensuring Reliable & Responsible AI Models (2024)
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E-commerce Big Data: Mining & Analytics for Online Success (2023)
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Building Data Science Apps with FastAPI: ML Deployment Guide (2023)
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Scalable Deep Learning on AWS: Develop, Train & Deploy AI (2025)
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Complex Decision Making with ML & Service-Oriented Computing (2023)
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Hyperparameter Tuning in R: ML & Deep Learning Guide (2023)
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Distributed ML with PySpark: Migrating from Pandas & Scikit (2023)
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Machine Learning with Scikit-Learn: Quick Start Guide
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Kernel Methods for ML: 100 Math & Python Exercises (2022)
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Automated Taxonomy Discovery: AI-Driven Data Exploration (2022)
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Machine Learning Essentials: Core Concepts & Techniques
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Robust Machine Learning: Distributed AI for Safe Systems (2024)
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Data Science Essentials: Analysis, ML & Visualization (2024)
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Learning Ray: Distributed Python for Machine Learning (2023)
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Machine Learning for Cybersecurity: Deep Learning Innovations (2022)
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Machine Learning with Rust: AI-Powered Development Guide
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AI & ML for Coders: Techniques, Tools & Real-World Applications
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Fundamentals of Machine Learning: Intro to Neural Networks (2024)
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Before Machine Learning Vol. 1: Linear Algebra for AI (2023)
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42 Essential Machine Learning Algorithms: A Practical Guide (2023)
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AI in Healthcare: Machine Learning’s Impact on Medicine (2025)
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NumPy Mastery: From Basics to Advanced for Machine Learning (2023)
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Google JAX Essentials: Fast Machine Learning & AI Projects
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Why Data Science Projects Fail: The Realities of AI & Analytics (2020)
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Essential Data Analytics, Data Science & AI: A Guide for 2025 (2025)
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Essential Data Analytics, Data Science & AI: A Guide for Data-Driven Decisions (2024)
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