MLOps Course in Hyderabad | MLOps Training Online

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: +91-9989971070 Visit: www.visualpath.in E-Mail: online@visualpath.in

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