8 ODSC Europe 2021 Talks We Can’t Wait to See

ODSC - Open Data Science
4 min readApr 19, 2021

It seems like only yesterday was ODSC Europe 2020. While we’ve still got a few months to go to ODSC Europe 2021 this June 8th-10th, we’re steadily confirming speakers for the biggest virtual data science featuring the best and brightest minds in AI from Europe. With plenty of talks to choose from and more in the pipeline, covering new focus areas and tracks, here are eight talks that we’re really excited about.

Highlighted ODSC Europe 2021 Talks

Model Governance: A Checklist for Getting AI Safely to Production

David Talby, PhD | CTO | Pacific AI, John Snow Labs

This talk summarizes the current best practices for model governance, along with freely available tools you can use today to apply them. Covered topics include Storing modeling assets in a searchable catalog — including notebooks, datasets, resulting measurements, hyper-parameters, and other metadata, and much more.

Mastering Gradient Boosting with CatBoost

Anna Veronika Dorogush | Machine Learning Lead | Yandex

This workshop will feature a comprehensive tutorial on using CatBoost library. We will walk you through all the steps of building a good predictive model, including working with different types of features, numerical, and categorical, working with inbalanced datasets, using cross-validation, and more.

Industrial Artificial Intelligence — From automated Process to Cognitive Analytics

Diego Galar, PhD | Professor of Condition Monitoring | Luleå University of Technology

The talk will show how the growth of industrial artificial intelligence is reimagining the industries in many dimensions. Companies are learning how to use their data to not only analyze the past but predict the future as well. Indeed, one industry that can expect to see unprecedented savings from AI is manufacturing where AI can usher in a new era of productivity.

https://odsc.com/europe/#register

Deep Learning for Anomaly Detection

Nisha Muktewar | Research Engineer | Cloudera Fast Forward Labs

This talk reviews a set of relevant deep learning model architectures including autoencoders, variational auto-encoders, generative adversarial networks and sequence-to-sequence methods, and addresses how they can be applied to the task of anomaly detection, comparing them in terms of training, inference, and storage costs.

Bayesian Data Science: Probabilistic Programming

Hugo Bowne-Anderson, PhD | Data Scientist | DataCamp

This tutorial will introduce you to the wonderful world of Bayesian data science through the lens of probabilistic programming in Python. In the first half of the tutorial, we will introduce the key concepts of probability distributions via hacker statistics, hands-on simulation, and telling stories of the data-generation processes. In the second half of the tutorial, we will use a series of models to build your familiarity with PyMC3.

The Colours of Cleaning

Marta Markiewicz | Senior Data Scientist, Lecturer | InPost, Wrocław University of Economics and Business

This session gathers the most helpful tricks and hacks with special emphasis on the usage of Machine Learning for cleaning tasks purposes. Pieces of advice are domain agnostic, so proposed approaches can be leveraged regardless of the business area of interest.

Machine Learning and Statistics: Don’t Mind the Gap

Thomas Wiecki, PhD | Director of Data Science | Quantopian

In this talk, we will look at the ideas that machine learning and statistics have developed, identify those that have already crossed the chasm, and those that are still grounded in one of the two fields. Some examples of such concepts are informative priors, neural networks, uncertainty, regularization, and hierarchical models.

Rule Induction and Reasoning in Knowledge Graphs

Daria Stepanova, PhD | Research Scientist | Bosch Center for AI

This tutorial presents state-of-the-art rule induction methods, recent advances, research opportunities as well as open challenges along this avenue. We put a particular emphasis on the problems of learning exception-enriched and numerical rules from highly biased and incomplete data.

Register for ODSC Europe 2021 Now

These talks are just a few of the sessions that will be available to you at ODSC Europe 2021 this June. For all of the currently confirmed sessions, you can check out the preliminary schedule here, and check out some highlighted half-day training sessions here.

Register now to save 30% on your ODSC Europe Pass, and take the first step toward getting the training you need to become a better data scientist.

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