Deploying Machine Learning Models
Examine the development and deployment of interactive Python data applications, with a particular emphasis on Recommender Systems and the use of Python web frameworks to deploy and monitor machine learning models.
Description for Deploying Machine Learning Models
Features of the Course:
Interactive Python Data Applications Project Structure: Acquire the ability to effectively organize and supervise the development of interactive Python applications for data-driven solutions.
Frameworks for Python web servers: Investigate frameworks such as Dash, Django, and Flask to develop web-based data applications.
Deployment Best Practices: Comprehend the optimal methods for the deployment of machine learning models and the monitoring of their performance in production environments.
Deployment scripts and APIs: Acquire practical experience in the development of APIs, serializing models, and deployment routines to facilitate the integration of machine learning models into applications.
Level: Intermediate
Certification Degree: Yes
Languages the Course is Available: 22
Offered by: On Coursera provided by University of California San Diego
Duration: 3 weeks at 3 hours a week
Schedule: Flexible
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