What You Need to Know Before
You Start
Starts 8 June 2025 04:24
Ends 8 June 2025
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Overview
Explore Java-based machine learning frameworks like Deeplearning4J, DJL, and Tribuo. Learn to build, save, and run ML models using Java, with real-world examples and comparisons.
Syllabus
- Introduction to Machine Learning in Java
- Java-Based Machine Learning Frameworks
- Building ML Models in Java
- Saving and Deploying Java ML Models
- Real-World Examples and Comparisons
- Practical Session: Developing a Complete Java ML Application
- Conclusion and Future Trends
- Additional Resources and Further Learning
Overview of Java's role in machine learning
Advantages and challenges of using Java for ML
Deeplearning4J
Introduction and setup
Core features and capabilities
Example project: Building a neural network
Deep Java Library (DJL)
Introduction and setup
Core features and capabilities
Example project: Image classification
Tribuo
Introduction and setup
Core features and capabilities
Example project: Regression model
Data preprocessing with Java
Defining and training models
Evaluating model performance
Model serialization and deserialization
Deployment strategies for Java ML models
Case studies of Java ML applications
Comparing Java ML frameworks: performance and use cases
Integrating multiple frameworks
End-to-end application development
The future of Java in machine learning
Emerging trends and technologies
Recommended books, online courses, and documentation
Community resources and support forums
Subjects
Conference Talks
