Name: Rust ML Online Meetup
Start: 2020-11-26T20:00:00+02:00
End: 2020-11-26T22:00:00+02:00

To access this webinar, please register here: https://aiplus.odsc.com/courses/rust-ml-online-meetup

Rust ML Online Meetup

This webinar is co-organized with Rust User Group - https://www.meetup.com/Rust-London-User-Group/

Talk title#1 - Speed is a feature. Introducing Fwumious Wabbit
Speaker#1: Andraz Tori, Head of Recommendations and Data Science at Outbrain
https://www.linkedin.com/in/andraz/
He Is the Head of Recommendations and Data Science at Outbrain, Zemanta co-founder, tech enthusiast and also ex-TV host.

Abstract#1:
Fwumious Wabbit is a Rust-based implementation of logistic regression and field aware factorization machines.
It runs on pure CPU and achieves extreme throughput compared to other similar tools. High throughput allows for quick turn around in machine learning applied research. It can be used for hyperparameter optimization or feature and field selection and combination. It also has an on-line serving mode and is being actively used in production.
In this presentation, we’ll present how extreme speed and throughput were achieved - using Rust strong code specialization capabilities and careful benchmarking and code-tuning.

Talk#2: Classical ML for Rust: linfa
Speaker: Paul Koerbitz PhD, Senior Software Engineer at Google
https://www.linkedin.com/in/paul-koerbitz-1276797/
Paul is a software engineer with a PhD in financial mathematics. After spending ~10 years in various startups, he currently works for Google.

Speaker: Lorenz Schmidt, M.Sc (RWTH Aachen University)
Lorenz has just finished his master studies and is now pursuing a doctoral program. He worked for companies on NLP and speech enhancement systems.

Abstract#2:
Meet linfa - Rust’s take on classical machine learning in the spirit of scikit-learn. Linfa’s current maintainers will tell you about linfa’s ambitious goals, its current state and the next steps forward. We’ll also touch on how to implement classical ML algorithms in Rust and how you can be part of the journey.

Talk#3: Multimodal Pronunciation Assessment in Rust
Speaker: Daniel McKenna, Software Engineer at Emotech
https://www.linkedin.com/in/daniel-mckenna-2ba1a772/
Daniel is a software engineer at Emotech, bringing machine learning to production with Rust. Before Emotech he spent 5 years working with C and C++ in aerospace and defense.

Abstarct#3:
This talk will cover Emotech’s Multimodal Pronunciation Assessment system which uses both audio and visual information to work out the quality of an English student's spoken pronunciation. This talk will cover some basic linguistics, the benefits of Rust, some of the existing ecosystem and the process of turning a python proof of concept into a production system.

Use discount code - Meetup2020 - to get an extra 10% off on your pass for Virtual Conference West and ODSC APAC. Extra discount applied over website prices - https://bit.ly/2AjFgQa

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Iryna Pidkovych

ODSC AI Tel Aviv

ODSC-AI-Community

Technology

Open Source

Python

Big Data

Machine Learning

Data Analytics

Data Visualization

Predictive Analytics

Data Science

Data Science using Python

Data Science using R

AI Algorithms

Artificial Intelligence

NLP (Neuro-Linguistic Programming)

Rust ML Online Meetup

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Rust ML Online Meetup

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