This Masterclass is designed to offer participants a comprehensive understanding of the essential stages in developing and deploying machine learning models. The main areas which will be covered in the masterclass are

• Data Preprocessing: Participants learn to clean, normalize, and transform data to make it suitable for model training, understanding the importance of quality input data.

• Model Training: This section delves into selecting appropriate algorithms, setting hyperparameters, and training models using the preprocessed data.

• Evaluation: Here, learners assess model performance using various metrics to ensure reliability and accuracy in predictions.

• Deployment: The final stage focuses on deploying the trained model into production environments, covering techniques for integrating models with existing applications for real-world use.

Designed for both beginners and intermediate learners, this masterclass emphasizes practical skills and theoretical knowledge, ensuring participants are well-equipped to handle real-world machine learning projects.