MLOps1 (Azure): Deploying AI & ML Models in Production using Microsoft Azure ML
The material equips data engineers to incorporate machine learning models into pipelines while adhering to best practices in collaboration, version control, and artifact management.
Description for MLOps1 (Azure): Deploying AI & ML Models in Production using Microsoft Azure ML
Collaborating with Data Scientists: Comprehend the essential abilities required for data engineers to collaborate effectively with data scientists.
Integration of Machine Learning: Acquire the skills to utilize machine learning models for predictive analytics and incorporate them into automated workflows.
Performance Evaluation: Assess the efficacy of models and pipelines while documenting pertinent indicators.
Versioning and Artifact Management: Implement optimal techniques for versioning models and data, and oversee the management of model and data artifacts.
Level: Intermediate
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On edX provided by Statistics.comX
Duration: 5�7 hours per week 4 weeks (approximately)
Schedule: Flexible
Pricing for MLOps1 (Azure): Deploying AI & ML Models in Production using Microsoft Azure ML
Use Cases for MLOps1 (Azure): Deploying AI & ML Models in Production using Microsoft Azure ML
FAQs for MLOps1 (Azure): Deploying AI & ML Models in Production using Microsoft Azure ML
Reviews for MLOps1 (Azure): Deploying AI & ML Models in Production using Microsoft Azure ML
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Featured Tools
Discover AI terminology, ethical norms, and protocols for responsibly utilizing and citing Generative AI.
This program instructs instructors on the ethical and successful integration of AI, while promoting innovation and critical thinking among students.
This course covers Python programming, TensorFlow for linear regression, and app development for stock market prediction.
Acquire an extensive understanding of reinforcement learning, deep neural networks, clustering, and dimensionality reduction to effectively address real-world machine learning challenges.
Explore the topic of AI-powered personalization by acquiring the skills necessary to utilize LangChain and ChatGPT.