Learn how to implement anomaly detection in your business applications with a complete, ready-to-use Delphi library. 7 anomaly detection algorithms: Three Sigma, Sliding Window, EMA, Adaptive, Isolation Forest, DBSCAN and LOF for fraud, errors and failures.
Complete guide to Graphviz DOT language for developers, analysts and software architects. Learn to create professional diagrams: flowcharts, software architectures, ER diagrams, state machines, dependency graphs and much more. With ready-to-use templates, commented examples and best practices for clear and versionable graphics.
DelphiMVCFramework introduces full support for WebSocket (RFC 6455), bringing bidirectional real-time communication to Delphi applications. Discover practical use cases for developers: chat, live dashboards, push notifications, IoT and much more. Both client and server implementation with ready-to-use examples.
WinInspector 2.1 introduces advanced features for Delphi and C++Builder developers: VCL Component Inspector for runtime analysis, complete DLL/Library Inspector with WOW64 bypass, intelligent auto-pause for in-depth analysis, and robust error handling. A professional tool for Windows developers.
In-depth analysis of PostgreSQL 18: Asynchronous I/O with 2-3x better performance, UUIDv7 for efficient primary keys, virtual generated columns, temporal constraints and much more. Complete guide with practical examples for Delphi and DelphiMVCFramework developers.
DelphiMVCFramework introduces native support for the Repository Pattern, enabling better separation of concerns, testability, and dependency injection in your REST APIs. Learn how to use IMVCRepository<T> with practical examples.
DMVCFramework introduces support for dynamic expressions in .env files through the $[expression] syntax, enabling mathematical calculations, logical operations, and string manipulation directly in configurations.
The reflection I bring to the classroom is always the same: we are inundated with the buzz around Large Language Models (LLMs), as if artificial intelligence were reduced to knowing how to chat. But while all the attention is there, another type of intelligence – silent, analytical, and devastatingly effective – continues to solve real business problems. This intelligence is classic Machine Learning, the art of making a machine learn from data.
In recent years, DelphiMVCFramework has been adopted in mission-critical systems worldwide: from banking APIs processing transactions worth millions of euros, to hospital systems managing vital patient data, to industrial platforms coordinating automated production lines. These systems share a common characteristic: they must handle millions of API calls daily while maintaining excellent performance and predictable response times. In such contexts, even seemingly simple operations can become critical bottlenecks when scaled to enterprise volumes. A perfect example is what you might encounter when developing a user registration API for a social network that has reached 100 million subscribers. Every time someone attempts to register, you need to verify if the email already exists in the database. An apparently innocent query like `SELECT COUNT(*) FROM users WHERE email = ?` may seem trivial, but when executed thousands of times per minute on a table with 100 million rows, even with the best indexes, the database starts to suffer.