MLOps Course in Hyderabad | MLOps Training Online

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1. MLOPS End-to-End MLOps: From Data to Deployment

2. Introduction to MLOps What is MLOps ? MLOps is the practice of combining machine learning (ML) with operations to streamline and automate the ML lifecycle .

3. The MLOps Lifecycle Phases of MLOps: Data Collection and Preparation Model Training and Validation Model Deployment and Monitoring Model Maintenance and Retraining

4. Data Collection and Preparation Data Collection: Sources of Data (Internal vs. External) Data Quality and Preprocessing Data Preparation: Data Cleaning and Transformation Feature Engineering

5. Model Training and Validation Model Training: Choosing Algorithms and Frameworks Training Techniques (Batch vs. Online) Model Validation: Cross-Validation Techniques Hyperparameter Tuning

6. Model Deployment and Monitoring Model Deployment: Deployment Strategies (Batch vs. Real-Time) Tools and Platforms (Kubernetes, Docker ) Model Monitoring: Performance Metrics (Accuracy, Precision, Recall) Detecting and Handling Drift

7. Model Maintenance and Retraining Model Maintenance: Regular Updates and Bug Fixes Continuous Integration and Delivery (CI/CD) for ML Model Retraining: Triggers for Retraining Automated Retraining Pipelines

8. Conclusion In summary , adopting an end-to-end MLOps approach enhances the efficiency and scalability of machine learning projects from data preparation to deployment. Key challenges , such as model drift and maintenance, can be managed with robust monitoring and automated retraining.

9. CONTAC Machine Learning Operations Training Address:- Flat no: 205, 2nd Floor, Nilgiri Block, Aditya Enclave, Ameerpet, Hyderabad-1 Ph. No: [phone]   Visit: www.visualpath.in E-Mail: [email protected]

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