Machine Learning
Machine Learning (ML) is a subfield of artificial intelligence where algorithms learn from data to recognize patterns and make predictions — without being explicitly programmed. ML encompasses supervised learning (with labels), unsupervised learning (clustering), and reinforcement learning (through rewards), forming the foundation of all modern AI systems.
Why does this matter?
ML is no longer a future technology but an operational reality: fraud detection in finance, demand forecasting in logistics, customer segmentation in marketing. Mid-sized businesses benefit most when ML is applied to existing, well-structured company data — that is where untapped potential lies.
How IJONIS uses this
We implement ML solutions built on your company data: forecasting models, classifiers, and anomaly detection. Our approach always starts with a data quality analysis — because no algorithm compensates for bad data. We use scikit-learn, XGBoost, and PyTorch depending on problem complexity.