Learning Path: Building Machine Learning Pipelines and Deploying ML Models From Scratch

Location: Golden Gate

Duration: 9:00am - 4:00pm

Day of week: Thursday, Friday

Level: Beginner

Key Takeaways

  • Understand the Machine Learning development process
  • Performing feature engineering with Apache Spark
  • Building Machine Learning pipelines and training Machine Learning models with Apache Spark
  • Gain a general understanding of Machine Learning model evaluation
  • Management Machine Learning models in terms of packaging and deployment with MLFlow

Prerequisites

  • Some programming experience
  • Please bring a Laptop

This ML Learning Path is designed to take attendees on a journey of learning on how to develop ML-powered applications by going through the well-known and proven Machine Learning development process. There are two main parts in this Learning Path. The first part will focus on performing feature engineering and developing Machine Learning pipelines and the second part will focus on developing, training and deploying Machine Learning models.

Attendees will gain a working knowledge of developing Machine Learning powered applications from end-to-end. You’ll learn how to leverage Apache Spark to perform feature engineering and developing ML pipelines, as well as manage and deploy an ML model with MLFlow.

Gain working knowledge about developing Machine Learning powered applications from end-to-end. Learn how to leverage Apache Spark to perform feature engineering and developing ML pipelines. Manage and deploy ML model with MLFlow.
 

Day 1 Topics

  • Apache Spark overview
  • Machine Learning overview
  • Feature engineering
  • Developing Machine Learning pipelines

Day 2 Topics

  • Training Machine Learning models
  • ML model evaluation and tracking with MLFlow
  • ML model deployment with MLFlow

Practical Elements

Gain working knowledge about developing Machine Learning powered applications from end-to-end. Learn how to leverage Apache Spark to perform feature engineering and developing ML pipelines. Manage and deploy ML model with MLFlow. 

Speaker: Hien Luu

Engineering Manager @Linkedin focused on Big Data

Hien Luu is an engineering manager at LinkedIn and he is a big data enthusiast. He is particularly passionate about the intersection between Big Data and Artificial Intelligence. Teaching is one his passions and he is currently teaching Apache Spark course at UCSC Silicon Valley Extension school. He has given presentations at various conferences like QCon SF, QCon London, Hadoop Summit, JavaOne, ArchSummit and Lucene/Solr Revolution.

Find Hien Luu at

Other Workshops:

Day: Friday [Full Day]
Day: Thursday [Half Day]
Day: Friday [Full Day]

Tracks

Monday, 11 November

Tuesday, 12 November

Wednesday, 13 November