Model Training
Train and tune your models with visual configuration.
Welcome to the Model Training section of ML Clever. This is where you transform your prepared data into powerful predictive models. Our platform offers flexible approaches, allowing you to either manually configure specific algorithms or leverage the efficiency of automated machine learning (AutoML). Whether you're tackling a regression problem (predicting numbers) or a classification task (predicting categories), ML Clever provides the tools to build, train, and evaluate models without writing complex code.
Fig 1: High-level Model Training Concept
Choose Your Training Approach
ML Clever offers two primary methods for training your models:
Manual Training
Configure and train your models manually.
Ideal for: Users who want precise control or need to use specific algorithms/parameters.
Explore Manual TrainingAutoML Training
Use automated machine learning for training.
Ideal for: Rapid exploration, benchmarking, or users seeking the best model without manual tuning.
Discover AutoML TrainingSupported Model Types
Depending on your defined task type, you can train models for:
Regression Models
Train models for regression tasks.
Example Task: Predicting house prices, forecasting sales, estimating temperature.
Learn about Regression ModelsClassification Models
Train models for classification tasks.
Example Task: Identifying spam emails, diagnosing diseases, classifying customer churn.
Explore Classification ModelsExplore Further
Dive deeper into the specific training methods and model types available by following the links above or using the detailed guides:
Configure and train your models manually.
Use automated machine learning for training.
Train models for regression tasks.
Train models for classification tasks.
Once your models are trained, the next logical step is to evaluate their performance. See the next section in the sidebar or click below:
Learn about Model Evaluation