Data Science Workstations

Take a deep dive into how workstations enable the AI journey in this four-part webinar series

Dell and Canonical

Part 1 - On demand

Data Pipelines

Explore the best open source platforms and tools that help to work on large and varying datasets

While new AI algorithms and training methods get all the hype, most analysts agree that data scientists spend up to 80% of their time on data: exploration, acquisition, ingestion, transformation and cleansing. This webinar will explore best open source platforms and tools that help to work on large and varying datasets, which is the first step of a four piece series on the AI Journey.

In this session we will talk about:
  • Data cleaning
  • ETL
  • Data governance
  • Data ingestion
  • Data types
  • Locality impacts on performance and security
Speakers:
  • Maciej Mazur - Product Manager at Canonical
  • Kyle Harper - Director of AI Strategy at Dell
  • Michael Boros - AI Strategy at Dell
Watch the webinar

Part 2 - June 8th | 11AM ET & 4PM BST

Choosing your algorithm

In this session we will talk about statistical computer vision, NLP, predictions, segmentation

Register

Part 3 - August 10th | 11AM ET & 4PM BST

Training on the workstation

In this session we will talk about, workstation vs server vs cloud, ephemeral environments, and GPU/acceleration

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Part 4 - Oct 12th | 11AM CT & 4PM BST

Deployment anywhere

In this session we will talk about Inference engines deployment

Register