Cloud Machine Learning Workflow and Content Delivery Optimization
Steps for Training a Machine Learning Project in the Cloud
Definition: Cloud ML Project Training
Training an ML Project in the Cloud means utilizing cloud-based resources and services to build, train, and optimize a Machine Learning model.
The Seven Key Steps in Cloud ML Training
- Data Collection: Gather and upload the dataset to cloud storage.
- Data Preprocessing: Clean and prepare data using cloud notebooks or specialized processing services.
- Model Selection: Choose the appropriate algorithm or utilize a pre-built model architecture.
- Training: Use scalable cloud compute resources (GPUs/TPUs) for intensive model training.
- Evaluation: Test model accuracy and performance using validation data.
- Hyperparameter Tuning: Optimize model parameters for better
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