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H2O.ai + source{d} Joint Meetup (TensorFlow.js + H2O Driverless AI)

Foto de Jo-fai Chow
Hosted By
Jo-fai C.
H2O.ai + source{d} Joint Meetup (TensorFlow.js + H2O Driverless AI)

Detalles

We are pleased to announce the next Madrid meetup on 7th November. Many thanks to source{d}, we have another excellent venue for this event.

Agenda:

  • Welcoming Remarks by Jo-fai Chow (H2O.ai)
  • Talk 1: TensorFlow.js by Vadim Markovtsev (source{d})
  • Talk 2: Introduction to H2O Driverless AI by Jo-fai Chow (H2O.ai)
  • Talk 3: Identifying Malicious Behaviour around Money Laundering by Ashrith Barthur (H2O.ai)
  • Refreshments + Networking

Note: All talks will be in English.

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Talk 1: TensorFlow.js by Vadim

Abstract:
TensorFlow.js enables training and applying ML models in a web browser or in node.js. To get a sense of the possibilities and limitations of the framework, we'll first have a go at a text classification problem, demonstrating the training and application of a model. Then we'll take a shot at the problem of inferring a function name given its code. This problem has interesting applications to create intelligent developer tooling. As a cool side effect, we will introduce ways to analyze code efficiently, with readily available open source software.

Bio:
Vadim Markovtsev (https://github.com/vmarkovtsev) is a Google Developer Expert in Machine Learning and a Lead Machine Learning Engineer at source{d} (sourced.tech) where he works with "big natural code". His academic background is compiler technologies and system programming. Vadim is an open source zealot and an open data knight.

References:

  1. something about modern JavaScript: https://github.com/micromata/awesome-javascript-learning
  2. something about TensorFlow: https://www.tensorflow.org/guide/low_level_intro and https://medium.com/the-artificial-impostor/notes-understanding-tensorflow-part-1-5f0ebb253ad4

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Talk 2: Introduction to H2O Driverless AI by Jo-fai Chow

H2O Driverless AI employs the techniques of expert data scientists in an easy to use application that helps scale your data science efforts. Driverless AI empowers data scientists to work on projects faster using automation and state-of-the-art
computing power from GPUs to accomplish tasks in minutes that used to take months.

With Driverless AI, everyone including expert and junior data scientists, domain scientists, and data engineers can develop trusted machine learning models. This next-generation automatic machine learning platform delivers unique and advanced functionality for data visualization, feature engineering, model interpretability and low-latency deployment.

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Talk 3: Identifying Malicious Behaviour around Money Laundering with by Ashrith Barthur

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H2O.ai Speakers:
Ashrith Barthur www.linkedin.com/in/abarthur/
Jo-fai (Joe) Chow www.linkedin.com/in/jofaichow/

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