Upgrade your machine learning models with graph-based algorithms, the perfect structure for complex and interlinked data.
In Graph-Powered Machine Learning, you will learn:
- The lifecycle of a machine learning project
- Graphs in big data platforms
- Data source modeling using graphs
- Graph-based natural language processing, recommendations, and fraud detection techniques
- Graph algorithms
- Working with Neo4J
Graph-Powered Machine Learning teaches to use graph-based algorithms and data organization strategies to develop superior machine learning applications. You’ll dive into the role of graphs in machine learning and big data platforms, and take an in-depth look at data source modeling, algorithm design, recommendations, and fraud detection. Explore end-to-end projects that illustrate architectures and help you optimize with best design practices. Author Alessandro Negro’s extensive experience shines through in every chapter, as you learn from examples and concrete scenarios based on his work with real clients!
