Ai+ Training

What's the Deal with Managed Services and Model Delivery?

Error Analysis for Accelerating Responsible Machine Learning

Benefits of Convolutional Neural Network for Healthcare Shortage Classification in Underserved Community

The Role of Data Virtualization in AI/ML Projects - A Demonstration

Enterprise ready ML Model Training on Hybrid Cloud, leveraging Kubernetes

The Colours of Cleaning

The Missing Link: How AI Can Help Create a Safer Society and Better Businesses

Deconstructing MLOps

Evolution of Efficient and Robust AutoML Systems by Frank Hutter, PhD

Industrial Artificial Intelligence – From Automated Process to Cognitive Analytics by Diego Galar, PhD

Most Popular Reasons ML Projects Fail and How to Avoid Them by Natasha Montagu

Incentives for Sociality: Intrinsic and Extrinsic Motivations of Social Dilemmas in Multi-Agent Systems by Edgar A Duenez-Guzman, PhD

Interpretable Machine Learning to Model Drug Perturbations in Single Cell Genomics by Dr. Fabian Theis

Finding that Needle! Modern Approaches to Fraud and Anomaly Detection by Aric LaBarr, PhD

Production Machine Learning Monitoring: Principles, Patterns and Techniques by Alejandro Saucedo

Meta-Learning: Learning to learn by Nisha Muktewar

Learning from Failure by Kamila Hankiewicz, Ivana Pejeva, Bogumił Kamiński

Smart City Data Pipeline, an Edge to Core Data Story by Guillaume Moutier

Exploring Modern and Secure Operations of Kubernetes Clusters on the Edge by Lucas Käldström

Building and Managing Advanced Analytics & AI Teams by John K. Thompson

What Do I See in This Data? Visual Tools to Enhance Data Understanding by Max Novelli

Model Governance: A Checklist for Getting AI Safely to Production by David Talby, PhD

Overcoming the Cold Start Problem: How to Make New Tasks Tractable by Azin Asgarian, Franziska Kirschner, PhD

Fairness in Medical Algorithms: Threats and Opportunities by Judy Gichoya

Women Ignite by Zakaria Tolba, Sharmistha Chatterjee, Cvetanka Eftimoska, Nutsa Abazadze, Hajar Khizou

Machine Learning for Planetary Health: Challenges, Opportunities, and Doing Our Bit by Sara Khalid

Exploring the Rimworld of Sound Space Using Generative Adversarial Networks by Laurens Koppenol, David Isaacs Paternostro

Building Real-Time ML Pipelines the Easy Way by Yaron Haviv

Keep it Simple: How to Talk to Executives in an Effective Way by Daniela Petruzalek

How I Became a Data Science Consultant and Other Stories by James Keirstead, PhD

Build your Own Job by Jack Raifer

Academia, Startups, and Enterprise: A Cross-Analysis of Work and Goals by Dan Shiebler

ML Data Challenges and Market Insights

Data Acquisition and Governance: Considerations for Success

The Next Evolution of PyTorch Performance Debugging

Integrating Data Science and Application Development

Feature Stores: Your MLOps Competitive Advantage by Adi Hirschtein

Comprehending ClearML and MLOps - Enabling the New A-Z

ML Observability: A Critical Piece in Making Models Work in the Real World by Aparna Dhinakaran

Augmented Intelligence: How Machine Learning + Human Analytics Catches Criminals by Danny Leybzon

Why is Data Virtualization a Data Scientist’s Best Friend? by Robin Tandon

Intro to Seldon Deploy: Deployment, Management and Monitoring of ML Models in Production by Tom Farrand

Neo4j Demo: Graph-Native Machine Learning and Predictions

Computer Vision: Seeing the Value for the Pixels - Lessons Learned from Real World Applications by Federica Citterio

Using News Analytics & Graphs to Inform Investment Decisions by Peter Hafez

Introduction to Transformers for NLP Where We Are and How We Got Here by Olga Petrova, PhD