Machine Learning Engineering for Production (MLOps) Specialization

Machine Learning Engineering for Production (MLOps) Specialization

Description

Machine Learning Engineering for Production (MLOps) Specialization is a training course to become a machine learning specialist. Understanding the concepts of machine learning and deep learning is essential, but if you’re looking to build an effective AI expertise, you’ll also need production engineering capabilities. Effective development of machine learning models requires competencies that are mostly found in areas such as software engineering and DevOps. Machine learning engineering for production is the result of combining the fundamental concepts of machine learning with the practical skills of modern software development and engineering roles.

In this specialty course, you will get to know the possibilities, challenges and results of machine learning engineering in production. At the end of the course, you can use your newly acquired skills in the development of cutting-edge artificial intelligence technologies to solve real-world problems.

Skills you will learn in the Machine Learning Engineering for Production (MLOps) Specialization:

  • Management of machine learning systems
  • Development, model and data Pipelines
  • Machine learning engineering for manufacturing
  • Doing work on a human level
  • Concept Drift
  • Model baseline
  • Challenges of machine learning development
  • Machine learning metadata
  • Convolutional neural network

Course details:

Publisher: Coursera
teacher: Andrew Ng, Cristian Bartolomé Arámburu, Robert Crowe And Laurence Moroney
English language
Training level: advanced
Number of courses: 4
Duration: assuming 5 hours of work per week, 4 months

Courses available in the Engineering Project Management Specialization series:

Course prerequisites:

Learners should have a working knowledge of AI and deep learning.
Learners should have intermediate Python skills and experience with any deep learning framework (TensorFlow, Keras, or PyTorch).
Learners should be proficient in basic calculus, linear algebra, and statistics.
We highly recommend that you complete the update Deep Learning Specialization before starting this specialization.

Pictures

Machine Learning Engineering for Production (MLOps) Specialization

Sample video

Installation guide

After Extract, view with your favorite Player.

Subtitles: English and other languages

Quality: 720

This collection includes 4 different courses.

To get quizzes, codes, etc., refer to these two links: Link 1 , Link 2

Course changes:

The 2021/9 version, compared to the 2021/7 version, includes the fourth course (Deploying Machine Learning Models in Production) along with course quizzes.

Version 2024/3 compared to version 2021/9 has increased by 1 lesson and 27 text files.

download link

Deploying Machine Learning Models in Productions

Download the course – 364 MB

Introduction to Machine Learning in Productions

Download the course – 617 MB

Machine Learning Data Lifecycle in Production s

Download the course – 390 MB

Machine Learning Modeling Pipelines in Productions

Download the course – 474 MB

Password file(s): www.downloadly.ir

Size

1.8 GB

4.4/5 – (6949 points)

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