Tag: Machine Learning

Machine Learning for Business: Boost Growth & Results

Why Machine Learning for Business Is No Longer Optional The business world is constantly evolving, and Machine Learning (ML) is at the forefront of this change. What was once a niche technology is quickly becoming a core requirement for businesses of all sizes. Companies experiencing significant growth are increasingly relying on ML to power their […]

Written by on May 1, 2025

NILG.AI Named Top ML Development Company

Many companies struggle to apply AI to real business problems without losing strategic focus. Today’s market is full of plug-and-play tools, generic AI solutions, and shiny features. As a result, staying focused on your strategy is more critical than ever. Rather than using AI just for innovation’s sake, companies should focus on how it can […]

Written by on Apr 20, 2025

Long-term vs. Short-term Predictions in Machine Learning

When building a machine learning model, one of the most common questions is whether to opt for long-term or short-term predictions. In other words, should you build a model that forecasts an event tomorrow or a month from now? Our article will demystify this critical decision-making process. We’ll walk you through a strategic approach that […]

Written by on Jan 27, 2024

Ditch the Crystal Ball: Reverse-Engineering with Machine Learning

  Machine Learning models are estimators – which means they can be used not only to predict unknowns in your business but also to reverse-engineer complex business processes. As part of this blog post, you will learn how to identify these potential points of improvement, prioritize them, and create models to estimate them. Identification How […]

Written by on Dec 27, 2023

Unleashing the Power of Open-Source Geospatial Data

Information is power, and geospatial data plays a vital role in various fields, including urban planning, transportation, environmental studies, and more. With the advent of machine learning, the demand for high-quality geospatial datasets has grown exponentially.  In the midst of this, you will find a lot of tools and product owners that will ask for […]

Written by on Oct 10, 2023

Classifying text using LLMs

  Text classification is one of the most common use cases in Natural Language Processing, with numerous practical applications – now easier to access with Large Language Models. Companies use text classification in multiple scenarios to become more efficient: Tagging large volumes of data: reducing manual labor with better filtering, automatically organizing large volumes of […]

Written by on Aug 29, 2023

Making Money with Mediocre AI Models

In the world of AI, it’s easy to assume that only the most accurate models can bring value to your business. However, this is far from the truth. In fact, even mediocre models can be transformed into money-making machines with the right strategies. In this article, we’ll explore three real-life examples of how we turned […]

Written by on Aug 15, 2023

Increasing Efficiency with Active Learning

The problem: Labeling data is boring (and expensive) So there you are. You have collected your data, analyzed it, processed it, and built your sophisticated model architecture. After many hours of training and evaluating, you have come to a very unpleasant conclusion: you need more data. Before you readjust your budget to fit the extra […]

Written by on Mar 3, 2023

NILG.AI among the winning startups of HODCON Challenge 2022

We are proud to announce that NILG.AI was among the winning startups of the open call for the Hands on Data 2022 Conference.  Hands on Data is an open innovation initiative that creates matchmaking opportunities between major corporations in the Ruhr area and global startups. From a pool of over 100 applications of start-ups from […]

Written by on Feb 13, 2023

How to deal with the annoying implications of changing data sources

Let’s discuss a common scenario in AI consulting. The client provides access to data sources in formats such as CSVs or databases that aren’t in a production environment. Why? Usually, they’re exploring the value of the project, do not want to disclose too much data and want to prevent technical problems from happening at the […]

Written by on Nov 20, 2022