[Packt] Machine Learning Projects with Java

Description

Machine Learning in Java: From Theory to Real-World Projects

Java isn’t just for enterprise backends—it’s a powerful, high-performance language for machine learning too. This Packt course takes you beyond toy datasets and teaches you to build production-ready ML applications in Java using libraries like WEKA, Apache Spark, and DL4J.

Why Learn ML in Java?

• Performance—Java runs faster than Python for large-scale data processing.
• Integration—seamlessly embed ML into existing Java/Android systems.
• Enterprise demand—banks, telecoms, and fintechs rely on Java for ML pipelines.

Real Projects You’ll Build

• Housing Price Predictor—linear regression on real estate data
• News Feed Classifier—NLP for categorizing unstructured text
• Sensor Pattern Recognizer—classify IoT device data using WEKA

Skills You’ll Gain

• Data preprocessing and feature engineering in Java
• Model training with WEKA and Smile libraries
• Evaluation metrics: accuracy, precision, recall, F1-score
• Deploying ML models as REST APIs with Spring Boot
• Optimizing performance with parallel streams and memory management

Who Is This For?

• Java developers expanding into data science
• Android engineers adding intelligent features to apps
• Enterprise devs in finance, logistics, or telecom
• Students needing Java-based ML for capstone projects

Java + ML = Career Superpower

While Python dominates ML tutorials, Java powers ML in production. This course gives you the rare combo that employers in Nigeria and globally pay a premium for.

Stop watching Python-only tutorials. Start building Java ML apps that scale.