Providing machine learning consulting services, we start with goal setting and analysis of business processes, then we help companies see machine learning capabilities matching their business goals.
By leveraging strong machine learning expertise, we handle all data-related processes, including data collection and preprocessing, to prepare datasets for effective modeling. We choose/create an optimal ML model, evaluating its accuracy to deliver production-ready solution tailored to specific business needs.
Our experts develop machine supervised, unsupervised and reinforcement learning solutions to deliver guaranteed value to clients.
With machine learning models trained on historical data, the tasks that demand forecasting, price predictions, seasonal fluctuations, and trends are solved much easier. Time series forecasting should become an integral part of the workflow for companies operating on markets with high volatility.
CodeIT Machine Learning specialists create applications to recognize, process, and interpret unstructured written and oral natural language to extract meaningful information and value. We help companies from various industries improve their daily workflows using NLP outcomes.
Based on machine learning algorithms, image analysis solutions can understand visual content and extract relevant information pertaining to object identification, recognition, and evaluation.
Leveraging machine learning capabilities, our data science team implements recommender systems critical in delivering personalized customer experience. Recommender systems are indispensable for e-commerce sites due to their ability of offering relevant suggestions to users.
Thus, we help companies win their customers’ loyalty, significantly increase conversions and boost revenue.
Predict market trends, behavior patterns, product sales, and more by extracting and analyzing past and present data. Predictive analytics will help predict and prevent potential issues, assess risks by ensuring better decision making.
The goal of anomaly detection is to identify unusual objects, events, or behavior in datasets that differ from the majority of data. The application of anomaly detection techniques is of great value in detecting intrusions, fraud, security issues, text data anomalies, health problems.