Conf42: Machine Learning 2021

July 29 2021

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Schedule

Event	Time	Location
Premiere Show introducing all talks and sponsors		Livestream
Keynote: From idea to production: Automate your machine learning workflows with pipelines Antje Barth Senior Developer Advocate - AI & ML at Amazon Web Services		Livestream
Keynote: Responsible AI in Health: From Principles to Practice Tempest van Schaik Biomedical Engineer at Microsoft		Livestream
All 23 talks available on demand Pick and choose what order to watch things in		Subscribe

Keynotes

From idea to production: Automate your machine learning workflows with pipelines

Developing high-quality machine learning models involve many steps. We typically start with exploring and preparing our data. We experiment with different algorithms and parameters. We spend time training and tuning our model until the model meets our quality metrics, and is ready to be deployed into production. Orchestrating and automating workflows across each step of this model development...

Antje Barth

Amazon Web Services

Responsible AI in Health: From Principles to Practice

AI has made amazing technological advances possible; as the field matures, the question for AI practitioners has shifted from “can we do it?” to “should we do it?”. In this talk, Dr. Tempest van Schaik will share her Responsible AI (RAI) journey, from ethical concerns in AI projects, to turning high-level RAI principles into code, and the foundation of an RAI review board that oversees projects...

Tempest van Schaik

Microsoft

TRACKS:

getting started security main tools lessons learned

Track: getting started

Convolutional Neural Networks in Action

Milecia McGregor

Iterative

Multilingual Natural Language Processing using Python

Gajendra Deshpande

KLS Gogte Institute of Technology

Track: security

Security at your fingertips: from Theory to Practice!

Madalina Burci

TypingDNA

Building ML environment for regulatory customers

Suraj Muraleedharan

AWS

Track: main

Monitoring AI Pipelines Output As Product

Hila Fox

Augury

Object Detection using Transformers and CNNs - A Drone Case Study

Eduardo Dixo

Continental

10 Things That Can Go Wrong with ML Projects (and what you can do about it)

Karl Weinmeister

Google

Seamless Customer Service with Amazon Connect and Alexa, using AI / ML

Asif Mujawar

AWS

Feature Engineering Techniques for Binary IoT Sensors

Nidal Albeiruti

AWS

Advanced machine learning time series forecasting methods review

Pawel Skrzypek

7bulls.com

Anna Warno

7bulls.com

Track: tools

Leverage Power of Machine Learning with ONNX

Ron Lyle Dagdag

Spacee

Search through your data with Weaviate and out-of-the-box machine learning models

Laura Ham

SeMI Technologies

Deploying ML solutions with low latency in Python

Aditya Lohia

Tod'Aers

Empower your business use cases by getting insights from text

Matteo Gabrielli

AWS

Serverless Deep Learning

Nicola Pietroluongo

AWS

E2E ML Platform on Kubernetes with just a few clicks

Mofizur Rahman

IBM

Natural language modelling with Amazon SageMaker BlazingText algorithm

Dinesh Subramani

AWS

Track: lessons learned

Deploying ML models and all the things that go wrong

Marianna Diachuk

Restream

History meets AI: Unveiling the secrets of ancient coins

Nicolas Metallo

AWS

Hail Hydrate! From Stream to Lake

Tim Spann

StreamNative

Pragmatic Machine Learning and ML Engineering in the Cloud with Amazon SageMaker

Joshua Arvin Lat

NuWorks Interactive Labs

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