Machine learning at scale in Azure Databricks
The future of data is AI and Machine Learning. Yet most companies still face challenges when building machine learning models. This is due to a myriad of reasons, ever-increasing dataset sizes, heavier computation cycles for state-of-the-art models, siloed analytics teams (and data sources) and many more. This is where Databricks helps immensely, providing a common data platform for analysts, engineers, developers and data scientists to collaborate, leveraging the efficiency of Apache Spark for distributed computing.
Advancing Analytics have developed a course based on the needs of our customers. This two-day course is for those intending to use Databricks to build machine learning models to solve real-world business use cases. You will learn how to build and tune ML models with SparkML while leveraging MLOps best practices. If you work in industries such as Financial Services, Retail, Healthcare, Media & Entertainment or any other industries and want to learn how to build machine learning models at scale, then this course is perfect for you.
Cost
On-site delivery: £1,100** per delegate (minimum 8 delegates)
Tailored course: POA
“The sessions were engaging, the content was easy to understand and pitched at the right level.”
Agenda
Day 1:
- The basic supervised and unsupervised machine learning models
- How to build real-world machine learning models with Databricks
- Learn all about the techniques for building a robust machine learning model
- The latest craze in machine learning, feature stores – a centralised approach to tracking model features!
Day 2:
- Advanced methods for tracking models – including the newly released MLFlow pipelines!
- Key considerations for scoring your models
- How to turn a black box model into something explainable
- Further model improvement techniques
If you would like to enquire about training then please complete the form below and we will get back to you.