Deep Learning World
May 24-28, 2021
Workshops take place the week before the conference on May 19-21, 2021
Blue circle workshops are for All Levels
Red triangle workshops are Expert/Practitioner Level
Machine Learning Workshops
The following analytics workshops do not pertain to deep learning, but cover other analytics topics and are available in the days before and after Deep Learning World as part of the co-located Predictive Analytics World events taking place at that time.
Wednesday, May 19
Big Data: The Leading Ways to Improve Business with Data Science (Non-Technical)
Full-day: 8:00am – 3:00pm PDT
This one day workshop reviews major big data success stories that have transformed businesses and created new markets.
Wednesday, May 19
Machine Learning with R: A Hands-On Introduction
Full-day: 7:30am – 3:30pm PDT
Gain experience driving R for predictive modeling across real examples and data sets. Survey the pertinent modeling packages.
Wednesday, May 19
The Best of Predictive Analytics: Core Machine Learning and Data Science Techniques
Full-day: 7:15am – 2:30pm PDT
This one-day session surveys standard and advanced methods for predictive modeling (aka machine learning).
Thursday, May 20
Ensemble Models: Supercharging Machine Learning
Full-day: 8:00am – 3:00pm PDT
This workshop dives into the key ensemble approaches, including Bagging, Random Forests, and Stochastic Gradient Boosting.
Thursday, May 20
Machine Learning with Python: A Hands-On Introduction
Full-day: 8:00am – 3:00pm PDT
Python leads as a top machine learning solution – thanks largely to its extensive battery of powerful open source machine learning libraries. It’s also one of the most important, powerful programming languages in general.
Thursday, May 20
Machine Learning Operationalized for Business: Ensuring ML Deployment Delivers Value
Full-day: 8:00am – 3:00pm PDT
Machine learning improves operations only when its predictive models are deployed, integrated and acted upon – that is, only when you operationalize it.
Thursday, May 20
Spark on Hadoop for Machine Learning:
Hands-On Lab
Full-day: 8:00am – 3:00pm PDT
Gain the power to extract signals from big data on your own, without relying on data engineers and Hadoop specialists.
James Casaletto
PhD Candidate
UC Santa Cruz Genomics Institute and former Senior Solutions Architect, MapR
Friday, May 21
The Deadly Dozen: The Top 12 Analytics Mistakes and the Techniques to Defeat Them
Full-day: 7:15am – 2:30pm PDT
This one-day session reveals the subtle mistakes analytics practitioners often make when facing a new challenge (the “deadly dozen”), and clearly explains the advanced methods seasoned experts use to avoid those pitfalls and build accurate and reliable models.
