Keynote: Ethics-Driven Development

In a world where computers, technology, programs and AI have increased impact on human lives, where do ethics belong?

In this talk, we'll look at a new paradigm called "Ethics-Driven Development" that utilizes ethical questions and goals to develop products that respect and inspire users.

We'll address issues of ethics in a data science team, asking: How can we integrate ethical goals into our design and feature specifications? What would it look like to incorporate ethic-focused metrics in our model selection process?

Using ethics-driven development, we will investigate processes, techniques and open-source tools to help you successfully integrate ethics into your development workflow.

 

Agenda

ab 8.30 Uhr Registrierung und Begrüßungskaffee

9.30 Uhr Beginn

Intro

Machine Learning

  • Was ist Machine Learning?
  • Der typische ML Workflow
  • Was sind neuronale Netze?
  • Jupyter Lab mit Python
  • Eine Einführung in TensorFlow
  • Keras als High-Level API für TensorFlow

Praxisteil: Deep Learning Modelle mit Keras

  • Datengeneratoren
  • Datasets explorativ analysieren
  • Hold-Out vs. Cross Validation

11.00 - 11.15 Uhr: Kaffeepause

Praxisteil: Deep Learning Modelle mit Keras

  • Feed-Forward Netzarchitektur
  • Convolutional Neural Networks als Deep Learning Ansatz
  • Evaluation und Visualisierung des Modells

12.30 - 13.30 Uhr: Mittagspause

Pipelines mit Luigi

  • Anforderungen an produktive Modelle
  • Übersicht über Luigi und dessen Module
  • Bau eines Beispiel-Workflows

Praxisteil: Den Keras-Workflow mit Luigi implementieren

  • Anforderungen an produktive Modelle
  • Übersicht über Luigi und dessen Module
  • Bau eines Beispiel-Workflows

15.30 - 15.45 Uhr: Kaffeepause

Praxisteil: TensorFlow-Serving

  • Übersicht über TensorFlow-Serving
  • Ladestrategien konfigurieren
  • Deployment des Modells

ca. 17.00 Uhr: Ende

 

Referent

 

Katharine Jarmul Katharine Jarmul is a pythonista and co-founder of KIProtect, a data security and privacy company for data science workflows in Berlin. She's been using Python since 2008 to solve and create problems. She helped form the first PyLadies chapter in Los Angeles in 2010, and co-authored an O'Reilly book along with several video courses on Python and data. She enjoys following the latest developments in machine learning, natural language processing, data privacy and ethics and workflow automation infrastructure and is generally chatty and crabby on Twitter, where you can keep up with her latest shenanigans.

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