What if machines could learn from their experiences just like humans do? Could they get smarter over time without being explicitly programmed? Let’s explore how Machine Learning makes this possible. Machine Learning (ML) is a key subset of Artificial...
RAG works well until it needs to understand how things are related. Retrieval-augmented generation (RAG) is a powerful technique that boosts the abilities of language models by combining two key steps: retrieving relevant information from an external...
In many modern AI applications, especially in search and retrieval, the ability to compare different types of content like text and images depends on one core idea: embeddings. These are fixed-size numerical vectors that capture the semantic meaning ...
While working on a recent project, I faced a challenge that seemed simple at first: I needed to generate embeddings for both images and text and use them together for retrieval. But the deeper I went, the more I realized the core issue — the image an...
Ever wondered how machines learn to make decisions? Before we teach a machine to learn, it's important to understand the algorithms and mathematics behind it. In this blog, we will apply the six steps from our previous post to build a Random Linear C...
The banking industry processes billions of transactions daily, making it a major target for fraudulent activities. Traditional fraud detection methods—rule-based systems, manual reviews by fraud analysts, or static thresholds with fixed limits—often ...