Ai+ Training

First Aid Kit for Data Science: Keeping Machine Learning Alive by Véronique Van Vlasselaer, PhD

eXplainable Predictive Decisioning: Combine ML and Decision Management to Promote Trust on Automated Decision Making by Matteo Mortariand Daniele Zonca

Build and Deploy Custom AI Predictive Models by Yamini Rao

A Quick, Practical Overview of KNIME Analytics Platform by Paolo Tamagnin

Best Practices: Partnerships between ML/AI and Data Labeling Companies by Soo Yang

An Overview of Algorithmia: the Industry Leading Machine Learning Operations and Management Platform by Kristopher Overholt

Leverage Data Lineage to Maximize the Benefits of Big Data by Ernie Ostic

Is Infrastructure Holding Back Adoption of AI at Scale? by Nick Patience

Revision Control for Structured Data by Gavin Mendel-Gleason

Sports Analytics - Leveraging Open Source Technology to Improve Athlete Performance by Christopher Connelly

Annotating Data with AI-assisted Labelling by Eric Landau

VerticaPy Demo : Building a Prediction Churn Model Using Random Forest & Logistic Regression by Badr Ouali

Creating Efficiency and Trust with MLOps by Jan van der Vegt

Build Your Own Cloud Native Covid-19 Data Analytics with Kubernetes and OpenShift by Dr. Mo Haghighi

Learn How to Seamlessly Use Julia for Your Machine Learning Tasks by Dr. Matt Bauman

Changing Career Paths: be a Data Scientist! by Bea Hernández

Demystifying Data Science Roles and Responsibilities by Eva-Marie Muller-Stuler, PhD

The Data Engineering Path by Daniela Petruzalek

Who is a Data Scientist? by Behrooz Afghahi

Navigating Data Science Interviews by Shrilata Murthy

Can Your Model Survive the Crisis: Monitoring, Diagnosis and Mitigation by Jiahang Zhong, PhD

Practical, Rigorous Explainability in AI by Tsvi Lev

Practical Methods to Optimise Model Stability: A Case Study Using Customer-Lifetime Value at Farfetch by Davide Sarra and Kishan Manani, PhD

Sprinting Pandas by Ian Ozsvald

A Gentle Intro to Transformer Neural Networks by Jay Alammar

Integrating Small Data, Synthetic Data in AI and Data Strategy for Fashion Retail by Andrey Golub, PhD

Knowledge Graphs for the Greater Good by Bojan Božić, PhD

Training a Machine to See What’s Beautiful (esp. for Hotel Photos) by Dat Tran

Knowledge Graph Extraction for the Enterprise by Dr. Paul Buitelaar and Dr. John McCrae

Making Happy Modelers: Build and Maintain Your Data Warehouse with AWS Redshift and Airflow by Stephanie Kirmer

Tracking Coal and Solar Power with Machine Learning and Satellites by Laurence Watson

Deep Learning for Anomaly Detection by Nisha Muktewar

Ensuring Ethical Practice in AI by Sray Agarwal

Forecasting the Economy with Fifty Shades of Emotions by Sonja Tilly, CFA

Sustainable Retail Through Open Source, Scraping and NLP by Joanneke Meijer

Image Detection as a Service: How we Use APIs and Deep Learning to Support our Products by Laura Mitchell

Beyond OCR: Using Deep Learning to Understand Documents by Eitan Anzenberg, PhD

Snakes on a Plane: Interactive Data Exploration with PyFlink and Zeppelin Notebooks by Marta Paes

Building Personalized Scores for Customers: How to Combine Different Data Types and Learn in the Process by Svetlana Vinogradova, PhD

Dare to Start Simple by Dr. Katharina Glass

Have I Got (Financial) News for You by Alun Biffin, PhD

Multivariate (Flight) Anomalies Detection by Marta Markiewicz

CRESST: Complete Rare Event Specification Using Stochastic Treatment by Debanjana Banerjee

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

Your Future, Today. Using NLP to Advance Your Career by Gabrielle Fournet, PhD

Machine Learning Operations: Latent Conditions and Active Failures by Flavio Clesio

Needles in a Haystack: Big Data and Bigger Promises? by Khurshid Ahmad, PhD

Which is the Tallest Building in Europe? — Representing and Reasoning About Knowledge by Ian Horrocks, PhD

Automated Insights in Finance Using Machine Learning & AI by Dr. Arun Verma

On the Automation of Data Science by Luc De Raedt, PhD

Leveraging Artificial Intelligence to Better Exploit Open Educational Resources by John Shawe-Taylor, PhD

VerticaPy: Demystifying Machine Learning Complexity with Python at Scale by Badr Ouali

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

Provenance: a Fundamental Data Governance Tool ⎯ a Case Study for Data Science Pipelines and Their Explanations by Luc Moreau, PhD

Algorithmic Confounding in Recommendation Systems by Allison Chaney, PhD

From Longitudinal Patient Observational Data to Individualized Treatments Effects Using Causal Inference by Ioana Bica

Predicting Future Decisions with Deep learning for Financial Trading by Ning Wang, PhD and Yuting Fu

Natural Language Processing: Feature Engineering in the Context of Stock Investing by Frank Zhao

Building Fair and Explainable AI Pipelines by Margriet Groenendijk, PhD

Cloud Platforms for AI - Why You Should Care About DevOps, Containers and Kubernetes by Steven Huels

Democratizing Data for the Enterprise by Sherard Griffin

The Evolution of Data Labeling by Soo Yang

At Last, a Good Night’s Sleep! Operationalizing your Models the Correct Way by Thodoris Petropoulos