Develop Production-Level Machine Learning Models using MLRun

Develop Production-Level Machine Learning Models using MLRun
Start Date: July 10, 2022
Last date to register: July 3, 2022
Course duration: 2 hours
Cost: free
Skill level: intermediate

Course Description

For whom is this course

Data Scientists and ML Engineers from students to seniors.

What you will learn

What are good habits in the 3 phases of a model’s life cycle – Data Preparation, Development, and Deployment.

  • How MLRun is built to adopt good habits into your work.
  • How MLRun integrates into existing code and enables quality of life features like Automatic Logging, Model Management, and Distributed Training.
  • Use MLRun’s model development tools to train classifiers on the classic, known, and loved Iris and MNIST datasets.

Prerequisites

  • Install MLRun on your computer
  • Work with Jupyter notebooks.
  • Very basic SciKit-Learn and TensorFlow background.

Syllabus

  • What is the model life cycle?
  • MLRun – The Open Source MLOps Orchestration Framework.
  • MLRun’s model development features – Automatic Logging, Model Management, and Distributed Training.
  • Iris demo – Train and deploy an Iris classifier.
  • MNIST demo – Train and deploy a handwritten digits classifier.

Course Features

Lectures: Hands on
Duration: 2 hours
Students: 50
Certificate: yes
Cost: free
Skill: intermediate

Video

Instructor

Guy Lecker
Machine Learning Engineer at Iguazio

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