MACHINE LEARNING COMPETENCIES
TIME SERIES FORECASTING
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.
NATURAL LANGUAGE PROCESSING
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.
COMPUTER VISION
Based on machine learning algorithms, image analysis solutions can understand visual content and extract relevant information pertaining to object identification, recognition, and evaluation.
ANOMALY DETECTION
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.
RECOMMENDER SYSTEMS
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.
Brand PREDICTIVE ANALYTICS
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.
TASK UNDERSTANDING
Define project requirements
Define task objective
DATA EXPLORATION
Discover data insights
Plot graphs, visualization
Domain knowledge reception
DATA PREPARATION
Data cleaning
Feature extraction
Feature selection
Build pre-processing pipeline
MODELING
Choose model
Define loss function and metrics
Parameter tuning
EVALUATION/VALIDATION
Performance scores estimation
Validation and test datasets evaluating
Cross-validation
DEPLOYMENT
Continuous model delivery
Prepare production-ready solution
Metrics logging
Performance monitoring
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