Live training with Mohamed Sabri starts on January 11th at 12 PM (EST)

Training duration: 4 hours (Hands-on)

Price with 30% discount

Regular Price: $210.00

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Instructor Bio:

Data Scientist Leader | MLOps engineer | Data science | Artificial Intelligence and Data Science Instructor | Rocket Science Development

Mohamed Sabri

Mohamed is fascinated by technology and information. He has a passion for data science (artificial intelligence, predictive analytics, business intelligence, etc.). Work and team cohesion is the secret to the success of all his professional and personal projects. He has published the book "Data Scientist Pocket Guide" that guides data scientists in their day to day and helps them learn some secrets to become good data scientists.

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Learning Objectives

  • Become familiar with Kubeflow

  • Learn how to work on Kubernetes environment

  • Building your first retraining pipeline

  • Move code from local to production (refactoring process)

DIFFICULTY LEVEL: INTERMEDIATE

Course Outline

MLOps 101 


- What is MLOps?

- MLOps is not just deployment

- MLOps is like DevOps but for ML

Kubernetes (10 minutes)

- Presentation of the technology

- Use cases 


Kubeflow


- Presentation of the technology

- Use cases

Presentation of the use case on Reddit (20 minutes)

- The business problem

- Current situation

- The architecture



Create the kubernetes cluster 


- Setup your AWS account

- Create the cluster


Pre-configuration and installation 


- Install necessary libraries on IDE

- Connect to AKS cluster


Initialize Kubeflow 


- Deploy kubeflow on AKS


Deploy a sample project


- Create a configuration file

- Deploy from UI


Deploy our use case pipeline


- Explore the notebooks

- Explore the pipeline

- Setup the cluster

- Deploy the pipeline

- Run the pipeline


Q&A 

Course Abstract

We will discover how to use Kubeflow to create a pipeline that retrains a machine learning model automatically and then redeploy the new model on top of an existing one. This process is a complex case that is common in MLOps. Allowing the company to automate the retraining and redeployment process. This material is based on 100% open-source tools that are most popular today in MLOps. This will help you master new set of tools that popularized in the field. The use case is unique based on Reddit data feed and based on a natural language process machine learning model that classifies text to detect inappropriate comments on the platform.

What background knowledge you should have?

  • Understanding of containerizationGood understanding of Python

  • Good understanding of Python

What is included in your ticket?

  • Access to live training and QA session with the Instructor

  • Access to the on-demand recording

  • Certificate of completion

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