Machine Learning Model
The end result of feeding data through a machine learning algorithm—a trained system that can make predictions, classify data, or perform some handy task. A machine learning model is like a crystal ball, only way more math-y and less about mysticism.
Machine Learning Algorithm
The step-by-step mathematical instructions that guide machine learning models to learn from data. Algorithms are the secret recipes that transform raw data into insights, predictions, or delightful accuracy (when they get it right).
Machine Learning
The science of getting computers to learn from data without being explicitly programmed for every task. Think of machine learning as teaching a machine to spot patterns, make predictions, and even surprise you with what it can figure out—minus the coffee breaks.
Loyalty Program
The gift that keeps giving. Loyalty programs reward repeat customers, keeping them coming back for perks, points, and prizes.
Low-Code Development
Coding for the non-coder. Low-code platforms let you build applications with drag-and-drop simplicity, reducing the need for heavy-duty programming.
Lo-Fi Prototype
The rough draft of design. Lo-fi prototypes show layout and functionality without the pretty details, focusing on what works, not just what looks good.
Load Testing
Pushing systems to their limits. Load testing checks how much traffic an application can handle before breaking, so you don’t end up with embarrassing downtime.
Load Balancing
Keeping the web stress-free. Load balancing spreads the workload across servers to prevent any one from overheating and crashing the party.
Load Balancer
Traffic cop for servers. A load balancer distributes incoming network requests evenly across multiple servers to keep everything running smoothly.
Liquidity Ratio
A quick snapshot of financial health. Liquidity ratios measure how easily a company can pay its bills without borrowing or selling its soul.