MLOps Training in Hyderabad | Machine Learning Operations Training

1. MLOPS Optimizing the Path from Model Creation to Deployment

2. Introduction • Overview of the complexities in transitioning ML models from research to production. • Highlight the gap between data scientists and operations teams. • Introduction to MLOps as a solution.

3. What is MLOps? • Definition: MLOps (Machine Learning Operations) combines ML, DevOps, and data engineering. • Focus on deploying and maintaining ML models in production. • Collaboration between data scientists, ML engineers, and operations professionals.

4. The Importance of MLOps • Reproducibility: Consistent model reproduction for debugging, improvement, and compliance. • Scalability: Scaling models and infrastructure with evolving models and data volumes. • CI/CD: Automating testing, data validation, model training, and deployment.

5. Key Stages of MLOps Pipeline • Data Management: Collecting, cleaning, and pre-processing reliable and representative data. • Model Development: Data exploration, feature building, and model training. • Model Validation: Validating models against separate datasets. • Deployment: Packaging models in containers and managing deployment.

6. Challenges in MLOps • Data and Concept Drift: Changes in data properties leading to performance degradation. • Versioning: Tracking versions of data, models, and code for reproducibility and debugging. • Infrastructure Management: Managing computing resources and storage. • Collaboration: Ensuring effective collaboration between data scientists, ML engineers, and operations teams.

7. Tools and Technologies in MLOps • Version Control: Git, DVC (Data Version Control). • CI/CD Tools: Jenkins, GitLab CI, CircleCI. • Model Serving: TensorFlow Serving, MLflow, Kubeflow. • Monitoring: Prometheus, Grafana, ELK stack.

8. Conclusion • MLOps bridges the gap between data science and production. • Ensures effective deployment, monitoring, and maintenance of ML models. • Drives innovation and value creation by leveraging the full potential of machine learning.

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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