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Introduction: What Are Adversarial Attacks and Data Manipulation in AI? Artificial intelligence models, especially those based on deep learning, have achieved remarkable success in fields such as image recognition, natural language processing, and autonomous systems. However, as these models become more widely adopted, their vulnerabilities are also becoming more apparent. Two of the most significant

Introduction to Generative Models Generative models are a cornerstone of modern artificial intelligence, enabling machines to create new data that resembles existing datasets. Unlike traditional discriminative models, which focus on classifying or predicting outcomes based on input data, generative models learn the underlying distribution of the data itself. This allows them to generate new, synthetic

Introduction to Neuro-Symbolic AI Neuro-symbolic AI is an emerging field that seeks to combine the strengths of neural networks with the capabilities of symbolic reasoning. This hybrid approach aims to bridge the gap between data-driven learning and structured, logic-based knowledge representation, offering new possibilities for building intelligent systems that are both powerful and interpretable. The

Introduction to AI Microservices The rapid evolution of artificial intelligence has driven organizations to seek scalable, flexible, and maintainable ways to deploy machine learning (ML) solutions. One of the most effective architectural paradigms to address these needs is the microservices approach. In this section, we explore what microservices are, why they are particularly beneficial for

Introduction to Custom Deep Learning Architectures The rapid evolution of deep learning has led to the development of a wide range of neural network architectures, many of which are available as ready-to-use models in popular frameworks. However, there are numerous scenarios where off-the-shelf solutions are insufficient, and designing a custom architecture becomes necessary. This introduction

Introduction to Model Optimization and Quantization Optimization and quantization of artificial intelligence models are key topics that enable increased computational efficiency and reduced hardware resource requirements. In the era of growing AI popularity, both in industrial and consumer applications, the ability to run advanced models on devices with limited computational power—such as smartphones, IoT devices,