Last updated 01/2023Duration: 1h 38m | Video: .MP4, 1280x720 30 fps | Audio: AAC, 48 kHz, 2ch | Size: 570 MBGenre: eLearning | Language: English[Auto]

 

It's not a course, it's all the best courses in one

What you'll learn

Understand the fundamental concepts of MLOps and its importance in the machine learning lifecycle

Learn how to deploy machine learning models in production using various MLOps tools and frameworks

Learn how to monitor and manage machine learning models in production

Understand the role of DevOps in MLOps and how to integrate the two practices

Learn how to implement best practices for MLOps, including version control, testing, and documentation

Requirements

Basic understanding of machine learning concepts

Familiarity with Python and Linux

Description

Our courses bring together the best resources from leading universities, companies, entrepreneurs and acads around the world to deliver a truly unparalleled learning experience.

Don't waste your money, our team of expert curators offers carefully curated education, providing the highest quality educational resources from the most respected institutions and industry leaders to create the ultimate MLOps Simplified course, an opportunity to acquire the best knowledge and skills in the field, providing the most efficient and effective types of objects.

THIS IS A EBOOK COURSE, A COMPILATION OF THE BEST EDUCATIONAL RESOURCES OF THE WORLD.

IT INCLUDES TEXTS, CODING EXAMPLES, CASE STUDIES AND OPTIONAL EVALUATIONS.

Course Description

MLOps, or Machine Learning Operations, is the practice of combining machine learning and operations to improve the speed and quality of deploying machine learning models in production. This course covers the latest techniques and tools used in MLOps, including model deployment, monitoring, and management.

Course Objectives

Understand the fundamental concepts of MLOps and its importance in the machine learning lifecycle

Learn how to deploy machine learning models in production using various MLOps tools and frameworks

Learn how to monitor and manage machine learning models in production

Understand the role of DevOps in MLOps and how to integrate the two practices

Learn how to implement best practices for MLOps, including version control, testing, and documentation

Course Outline

Week 1: Introduction to MLOps

Introduction to MLOps and its importance in the machine learning lifecycle

Overview of the machine learning lifecycle and the role of MLOps in each stage

Week 2: Model Deployment

Introduction to model deployment

Techniques for deploying machine learning models in production

Hands-on deployment using various MLOps tools and frameworks

Week 3: Model Monitoring and Management

Introduction to model monitoring and management

Techniques for monitoring and managing machine learning models in production

Hands-on monitoring and management using various MLOps tools and frameworks

Week 4: DevOps and MLOps Integration

Introduction to DevOps and its importance in MLOps

Techniques for integrating DevOps and MLOps practices

Hands-on integration using various MLOps tools and frameworks

Week 5: MLOps Best Practices

Introduction to best practices for MLOps

Implementing version control, testing, and documentation in MLOps

Hands-on implementation using various MLOps tools and frameworks

Week 6: Capstone Project

Students will work on a capstone project to apply the skills and knowledge learned in the course

Students will present their projects to the class

Who this course is for

The course would be beneficial for anyone interested in learning more about MLOps and its importance in the machine learning lifecycle.