MLOps with MLFlow – (Pre-Order)

MLOps is becoming more and more popular. The most popular framework in this niche is the MLFlow Framework.  Do you need to create trackable, reproducible and scalable Machine Learning Applications? MLFlow is a Machine Learning Framework for small and enterprise level ML Projects. With this Mlflow Online Course you’ll learn MLFlow from scratch. This is a Pre-Order Course – still in development.


(1 customer review)

Chapter 1 : Documentation Look Around

Exploration of the new MLOps area. Introduction to  MLFlow Machine Learning Framework.


Chapter 2 : Installation & Dependencies

We’ll need to install Conda and Docker for MLFlow. Of course we are going to cover the basics of Docker.


Chapter 3 : Concepts Overview

The three main pillars of MLFlow are:

  • MLFlow Tracking
  • MLFlow Projects
  • MLFlow Models




Chapter 4 : MLFLow Tracking

 Mlflow Tracking is an API and UI for logging parameters, code versions, metrics, and output files when running your machine learning code and for visualizing.


Chapter 5 : MLFLow Model

MLflow Model is a format for packaging machine learning models that can be used in a variety of downstream tools—e.g real-time serving via REST API or batch inference on AWS Sagemaker.


German IT Academy

✔️  100% Online

✔️  Low Difficulty 

✔️  English Content

✔️  Practical Insights

✔️  Best Practice Tips

✔️  Certificate of Attendance

✔️  Worldwide recognition

Andrey Bulezyuk


Andrey Bulezyuk is the founder of German IT Academy and an Instructor. He covers topics from Web Development, Data Science, Machine Learning.

He published a Book “Algorithmic Trading“, giving his readers the opportunity to learn how to code automatic trading systems for the Stock Market. 

Bonus Material

We always try and make our customers happy with some extra bonus material. There is a small surprise content waiting for you.

Personal Coaching

Is the topic of this course very critical for your mission? Our Coaches are available for personal or in-house coaching.

Ready to get started?

1 review for MLOps with MLFlow - (Pre-Order)

  1. Aditya A.

    Everything was good.

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