model-trained

Model training is the phase in machine learning where algorithms learn patterns from a given dataset to make predictions or decisions. During this process, the model adjusts its parameters based on the input data and the output labels, optimizing its performance. Effective model training requires a well-prepared dataset, appropriate algorithms, and careful tuning of hyperparameters to achieve the best results.