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AI and ML developers often work with local datasets while preprocessing data. Engineering features, and building prototypes make this easy without the overhead of a full server. The most common comparison is between SQLite, a serverless database released in 2000 and widely used for lightweight transactions, and DuckDB, introduced in 2019 as the SQLite of analytics, focused on fast in-process analytical queries. While both are embedded, their goals differ. In this article, we’ll compare DuckDB and SQLite to help you choose the right tool for each stage of your AI workflow. What is SQLite? SQLite is a self-contained database engine…

Image by Author   # Introduction  AI coding tools are getting impressively good at writing Python code that works. They can build entire applications and implement complex algorithms in minutes. However, the code AI generates is often a pain to maintain. If you are using tools like Claude Code, GitHub Copilot, or Cursor’s agentic mode, you have probably experienced this. The AI helps you ship working code fast, but the cost shows up later. You have likely refactored a bloated function just to understand how it works weeks after it was generated. The problem isn’t that AI writes bad code —…

Large language models are great. We all can agree to that. They’ve been a cornerstone of modern industry and are increasingly impacting more and more domains.  With constant upgrades and improvements to the architecture and capabilities of language models, one might think – That’s it! Alas… A recent development under the name of RLM or Recursive language models, have taken the centerstage now.  What is it? How does it relate to LLMs? And how does it push the frontier of AI? We’ll find out in this article which dissects this latest technology in an accessible manner. Let’s begin by going over…

Image by Author   # Introduction  When building machine learning models with moderate to high complexity, there is an ample range of model parameters that are not learned from data, but instead must be set by us a priori: these are known as hyperparameters. Models like random forest ensembles and neural networks have a variety of hyperparameters to be adjusted, such that each one can take one of many different values. As a result, the possible ways to configure even a small subset of hyperparameters become nearly endless. This entails a problem: identifying the optimal configuration of these hyperparameters — i.e.…

Imagine stepping into your first data science interview—your palms are sweaty, your mind racing, and then… you get a question you actually know the answer to. That’s the power of preparation. With data science reshaping how businesses make decisions, the race to hire skilled data scientists is more intense than ever. For freshers, standing out in a sea of talent means more than just knowing the basics—it means being interview-ready. In this article, we’ve handpicked the top 100 data science interview questions that frequently appear in real interviews, giving you the edge you need. From Python programming and EDA to…

Image by Author   # Introduction  Working with JSON in Python is often challenging. The basic json.loads() only gets you so far. API responses, configuration files, and data exports often contain JSON that is messy or poorly structured. You need to flatten nested objects, safely extract values without KeyError exceptions, merge multiple JSON files, or convert between JSON and other formats. These tasks come up constantly in web scraping, API integration, and data processing. This article walks you through five practical functions for handling common JSON parsing and processing tasks. You can find the code for these functions on GitHub.  # 1.…

Gemini 3 and NotebookLM are two of my favorite tools from the Google suite. I use them often for learning, work, and even for breaking down complex ideas in a simple way. But this time, I wanted to do something purely fun. Lately, I’ve been seeing AI-generated comics all over social media. From story writing to visuals and final layouts, everything is created using AI. Curious to see how practical this really is, I decided to try it myself. In this blog, I document my experiment of creating a full comic using Gemini 3 and NotebookLM from idea to final output. If…

We interact with LLMs every day. We write prompts, paste documents, continue long conversations, and expect the model to remember what we said earlier. When it does, we move on. When it doesn’t, we repeat ourselves or assume something went wrong. What most people rarely think about is that every response is constrained by something called the context window. It quietly decides how much of your prompt the model can see, how long a conversation stays coherent, and why older information suddenly drops out. Every large language model has a context window, yet most users never learn what it is or…

Just as you wouldn’t teach a child to ride a bike on a busy highway, AI agents need controlled environments to learn and improve. The environment shapes how an agent perceives the world, learns from experience, and makes decisions, whether it’s a self-driving car or a chatbot. Understanding these environments is essential to building AI systems that work reliably. In this article, we explore the different types of environments in AI and why they matter. What is an Environment in AI  In AI, an environment is a stage where AI agents perform its role. Think of it as the complete…

In recent times, if you have been delving into the development of AI, then you may have come across the term ‘agent frameworks.’ Today, we are going to discuss one of them, the Strands Agents. This is a tool that is altering the way developers create intelligent systems. But if you are a beginner, you need not worry; we will guide you through everything in a simple way in this article. What are Strands Agents? Consider Strands Agents as the integrated operation of your AI’s brain and body. Unlike conventional chatbots that only react to your input, these agents can…