Applied Machine Learning: A Practical Guide to Preparing Data, Selecting Algorithms, and Implementing Machine Learning Models in the Real World Available at http://
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Applied Machine Learning: Practical Guide for Real-World Implementation
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Introduction to Probability, Statistics, and Random Processes Book
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AI-Powered Qualitative Data Analysis: ChatGPT QualCoder Guide
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Illustrated Guide to Neural Networks and AI with PyTorch Examples
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Illustrated Guide to Neural Networks and AI — With hands-on examples in PyTorch: http://
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Feature Engineering for Modern Machine Learning with Scikit-Learn
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Feature Engineering for Modern Machine Learning with Scikit-Learn: Advanced Data Science and Practical Applications (Advanced Data Analysis Series) Available at http://
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Platform and Model Design for Responsible AI Systems
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Platform and Model Design for Responsible AI — Design and build resilient, private, fair, and transparent machine learning models: http://
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Machine Learning and Artificial Intelligence: Concepts, Algorithms and Models
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Machine Learning and Artificial Intelligence: Concepts, Algorithms and Models Available at http://
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Classic Text on Outlier Detection in Temporal Data Streams
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Classic text on Outlier Detection in Temporal Data: http://
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Analytical Skills for AI and Data Science in Enterprise
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Analytical Skills for AI and Data Science — Building Skills for an AI-Driven Enterprise: http://
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Learn Probability Through Problems with Exercises and Solutions
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Learn Probability Through Problems (exercises, hints, and solutions provided): http://
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