GitHub

dbt Model Planner

Turn schema requirements into production dbt models through a structured, iterative planning process. This skill ensures nothing gets built before the mapping is validated — saving rework and catching ...
marktechpost

Safely Deploying ML Models to Production: Four Controlled Strategies (A/B, Canary, Interleaved, Shadow Testing)

Deploying a new machine learning model to production is one of the most critical stages of the ML lifecycle. Even if a model performs well on validation and test datasets, directly replacing the ...
GitHub

Class 2 - SQL Fundamentals and Practice

(15, 23, 2, 149.00); -- Himalaya Face Wash x2 ...
IEEE

From Large AI Models to Agentic AI: A Tutorial on Future Intelligent Communications

Abstract: With the advent of 6G communications, intelligent communication systems face multiple challenges, including constrained perception and response capabilities, limited scalability, and low ...
marktechpost

A Complete End-to-End Coding Guide to MLflow Experiment Tracking, Hyperparameter Optimization, Model Evaluation, and Live Model Deployment

In this tutorial, we build a complete, production-grade ML experimentation and deployment workflow using MLflow. We start by launching a dedicated MLflow Tracking Server with a structured backend and ...
IEEE

A Hybrid Deep Learning Model for SQL Injection Attack Detection

Abstract: An increasing number of web application services raises significant security concerns. Online access to these applications exposes them to multiple cyberattacks. The Open Web Application ...
Scientific Research Publishing

Designing a Detection Model for SQL Injection Attack ()

SQL injection attacks pose a critical threat to web application security, exploiting vulnerabilities to gain access, or modify sensitive data. Traditional rule-based and machine learning approaches ...