Browsing: Business & Startups

  # Introduction  Anyone who has spent a fair amount of time doing data science may sooner or later learn something: the golden rule of downstream machine learning modeling, known as garbage in, garbage out (GIGO). For example, feeding a linear regression model with highly collinear data, or running ANOVA tests on heteroscedastic variances, is the perfect recipe… for ineffective models that won’t learn properly. Exploratory data analysis (EDA) has a lot to say in terms of visualizations like scatter plots and histograms, yet they aren’t sufficient when we need rigorous validation of data against the mathematical assumptions needed in downstream…

Feature engineering is the foundation of strong machine learning systems, but the traditional process is often manual, time-consuming, and dependent on domain expertise. While effective, it can miss deeper signals hidden in unstructured data such as text, logs, and user interactions. Large Language Models change this by helping machines understand language, extract meaning, and generate richer features automatically. This shift opens new ways to build smarter ML pipelines. This article offers a practical guide to feature engineering using LLMs. What is Feature Engineering with LLMs? The process of feature engineering with LLMs uses large language models to develop and modify…

  # The Plot Thickens  You’ve probably heard someone say “that’s a normal distribution” like it’s a magic spell that explains everything. Truth is, distributions are just stories about how numbers tend to show up in real life. Some stories are smooth curves. Some are lumpy. Some are basically a coin flip with better branding. This article is a quick, everyday tour of seven distributions you’ll actually recognize once you know what to look for. No heavy math. No gatekeeping. Just the vibe of: “Ohhh, that’s why those numbers behave like that.” Once you start spotting these patterns, stats stops feeling…

  # Introduction  Claude Code Channels is quickly becoming a practical alternative to OpenClaw for people who want to connect Claude to chat platforms without setting up a heavier agent framework. It is simpler to get running, works with a Claude subscription out of the box, and gives you a straightforward way to interact with a local Claude Code session through Discord. In this article, you will learn how to set up Claude Code Channels locally and connect it to your Discord server. The key thing to understand from the start is that this setup depends on a live local Claude…

Sponsored Content      The artificial intelligence market is crowded with a lot of things like chatbots and writing assistants and image generators and coding tools and automation platforms and agent builders. Most of these things only solve one problem. Abacus AI is trying to solve a bigger problem: it wants to give people and teams one artificial intelligence system that can do a lot of things. This system can chat with people. Do research and build things and automate tasks and generate media and create apps and run persistent agents. Abacus AI is one of the ambitious artificial intelligence…

The headline may sound extreme here. Of course, Claude is not replacing CFOs tomorrow morning. But with the debut of Claude’s new Financial Services Solution by Anthropic, it has clearly moved to a new direction in the world of finance, one where AI does way more than crunch numbers or explain stuff. Think specific financial tasks, like KYC screening, GL reconciliation, statement audit, and month-end closer. That’s right, these are the exact projects many teams spend weeks on, all done in a matter of minutes now. The seemingly revolutionary abilities are not part of a new model. These are being…

  # Introduction  OpenCode plugins are add-ons that extend the capabilities of the OpenCode AI coding agent. They provide extra tools, integrations, and workflow enhancements such as persistent memory, terminal access, cited web search, reusable skills, and analytics. These plugins help developers customize OpenCode for more advanced coding, research, and automation workflows. In this article, we review seven OpenCode plugins that stand out for their usefulness, features, and growing adoption in the community. Together, they show how plugins can make the OpenCode agent more powerful, flexible, and practical for everyday use.   # 1. Oh My Openagent  Widely regarded as the most…

  # Introduction  Before we start, let’s quickly revisit what Claude Code is and why it is useful to learn. Claude Code is an agentic coding tool from Anthropic that can read your codebase, edit files, run commands, fix bugs, write tests, create commits, and connect with external tools through Model Context Protocol (MCP). It works in the terminal, integrated development environments (IDEs), desktop app, browser, and other development environments, making it useful for both small experiments and more serious software projects. In this article of our “5 Fun Projects” series, you will learn by doing. The projects start with a…

  # Introduction  Every organization loves to call itself “data-driven.” It’s become the gold standard of credibility, the thing you say to shut down dissent in a meeting. But here’s something worth sitting with for a second: the phrase “according to data analytics” can come from two very different places. One is genuine curiosity. The other is someone who already knows what they want and went looking for a number to back it up. And the weird part? Both of those people end up pushing for the same decision, using the same language, sitting on the same side of the table.…

Fine-tuning LLMs has become much easier because of open-source tools. You no longer need to build the full training stack from scratch. Whether you want low-VRAM training, LoRA, QLoRA, RLHF, DPO, multi-GPU scaling, or a simple UI, there is likely a library that fits your workflow. Here are the best open-source libraries worth knowing for fine-tuning LLMs locally. From faster speeds to reduced load, all of them have something to offer. 1. Unsloth Unsloth is built for fast and memory-efficient LLM fine-tuning. It is useful when you want to train models locally, on Colab, Kaggle, or on consumer GPUs. The…