MLOps Course in Hyderabad | Machine Learning Training in Ameerpet
- 1. MLOPS Bridging the Gap Between Machine Learning and Operations
- 2. Introduction to MLOps What is MLOps? • Definition: MLOps (Machine Learning Operations) is a set of practices to deploy and maintain machine learning models in production reliably and efficiently. • Goal: Integrate ML system development (Dev) and operations (Ops).
- 3. Importance of MLOps Why MLOps? • Scalability: Ensures models can handle production- level workloads. • Reproducibility: Facilitates consistent and repeatable processes. • Collaboration: Enhances collaboration between data scientists and operations teams. • Monitoring: Continuous monitoring of model performance and health.
- 4. MLOps Lifecycle 1. Data Collection: Gather and pre-process data. 2. Model Development: Train and validate machine learning models. 3. Deployment: Deploy models into production. 4. Monitoring: Continuously monitor model performance. 5. Maintenance: Update and retrain models as needed.
- 5. Key Components of MLOps • CI/CD Pipelines: Continuous Integration and Continuous Deployment. • Version Control: Tracking changes in data, code, and models. • Automated Testing: Ensuring model quality and performance. • Infrastructure Management: Managing computational resources.
- 6. CI/CD in MLOps • Continuous Integration (CI): Automated testing and integration of code changes. • Continuous Deployment (CD): Automated deployment of models to production environments
- 7. MLOps Tools and Technologies • Version Control: Git, DVC • CI/CD: Jenkins, GitHub Actions • Model Training: TensorFlow, PyTorch • Deployment: Kubernetes, Docker • Monitoring: Prometheus, Grafana
- 8. Challenges in MLOps • Data Management: Handling large volumes of data. • Model Versioning: Tracking changes and updates. • Infrastructure Complexity: Managing diverse tools and platforms. • Collaboration: Bridging the gap between data scientists and IT operations.
- 9. Future of MLOps • Trends: Increased automation, more robust tools, integration with AI and IoT. • Opportunities: Enhanced predictive analytics, real-time processing, improved model management.
- 10. 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: [email protected]