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PHP and Machine Learning: A Practical Introduction for Web Developers: A Practical Guide to ML Fundamentals, Real-World Applications, and Python Integration - Softcover

 
9798288737053: PHP and Machine Learning: A Practical Introduction for Web Developers: A Practical Guide to ML Fundamentals, Real-World Applications, and Python Integration

Synopsis

What You Will Learn in This Book

  • Understand the fundamentals of machine learning (ML), including supervised, unsupervised, and reinforcement learning, and their relevance to web development.
  • Set up a robust PHP development environment for ML, integrating essential tools like Composer and the PHP-ML library.
  • Implement core machine learning algorithms directly in PHP using PHP-ML, covering classification (e.g., spam detection, sentiment analysis), regression (e.g., price prediction), and clustering (e.g., customer segmentation).
  • Master data preprocessing and feature engineering techniques to prepare diverse datasets for ML models, including handling missing data, normalization, and text preprocessing.
  • Perform advanced data acquisition and manipulation using core PHP, reading from various sources like CSV, JSON, XML, databases, and APIs, and efficiently cleaning and transforming data.
  • Seamlessly integrate PHP applications with powerful Python-based ML services, leveraging popular frameworks like Scikit-learn, TensorFlow, and PyTorch.
  • Implement various PHP-Python integration strategies, including executing Python scripts, consuming REST APIs, utilizing message queues for asynchronous tasks, and understanding gRPC for high-performance communication.
  • Design and build hybrid PHP/Python applications through practical case studies, demonstrating how to combine PHP for frontend and data management with Python for complex ML model training and serving.
  • Gain insights into advanced ML topics such as deep learning and natural language processing, understanding when and how to integrate these capabilities into your PHP projects.
  • Learn best practices for deploying and maintaining ML models within PHP applications, including saving/loading models and monitoring performance.
  • Develop an awareness of the limitations of PHP in ML and ethical considerations, ensuring responsible and informed application of machine learning in your projects.

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Publishing, PhiQuill
Published by Independently published, 2025
ISBN 13: 9798288737053
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