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

By PhiQuill Publishing

What You Will Learn in This BookUnderstand 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.

• Format: Paperback
• Language: English
• ISBN: B0FDWP3KSJ
• ISBN13: 9798288737053
• Release Date: June 2025
• Publisher: Independently Published
• Length: 160 Pages
• Weight: 0.85 lbs.
• Dimensions: 0.3" x 8.5" x 11.0"