Ai+ Training

A Decade of Machine Learning Accelerators_ Lessons Learned and Carbon Footprint by David Patterson, PhD

AI in a Minefield_Learning from Poisoned Data by Johnathan Roy Azaria

Denoising Diffusion-based Generative Modeling by Stefano Ermon, PhD

Toward Robust, Knowledge-Rich Natural Language Processing by Hannaneh Hajishirzi, PhD

Operationalizing Organizational Knowledge with Data-Centric AI by Alex Ratner, PhD

Inclusive Search and Recommendations by Nadia Fawaz, PhD

How the Changing MLOps Landscape is Reinventing DataOps by Rajsekhar (Raj) Aikat

The Next Thousand Languages by Steven Bird, PhD

An Intuition-Based Approach to Reinforcement Learning by Oswald Campesato

Introduction to Generative Art with Stable Diffusion, presented by HP Inc by Hunter Kempf

Real-time Data Science Made Easy by Chip Kent

Emerging Approaches to AI Governance_Tech-Led vs Policy-Led by Ilana Golbin

Look, Listen, Read:Unified AI with TorchMultimodal by Suraj Subramanian and Evan Smothers

Continual Learning of Natural Language Processing Tasks by Bing Liu, PhD

Why you can’t Apply Common Software Best Practices Directly to Data Workflows, and What you can do About it by Anna Filippova

Data Science Without Data Collection Using FedScale by Mosharaf Chowdhury, PhD

A Tale of Adversarial Attacks & Out-of-Distribution Detection Stories in the Activation Space by Celia Cintas, PhD

Open-source Data Curation and Governance for Large and Growing Data Lakes by Roger Dev

Rethinking ML Development - A Data-Centric Approach by Jimmy Whitaker

Impact of Data Science on Social Media Data by Jyotika Singh

Graph Data Science:The Secret Ingredient for Relationship-Driven AI by Katie Roberts, PhD

Four Reasons the Data Science Development Experience Sucks by Greg Michaelson, PhD

Data Analytics at Scale:A Four-legged Stool by Michael Stonebraker, PhD

Unified and Efficient Multimodal Pretraining Across Vision and Language by Mohit Bansal, PhD

Interpretable AI or How I Learned to Stop Worrying and Trust AI by Ajay Thampi, PhD

Causal AI by Robert Osazuwa Ness, PhD

AI TCO (Total Cost of Ownership) Considerations from Pilot to Production Scale by Justin Emerson

Search and Discovery in News and Research by Dr. Anju Kambadur

DS-AI for Incident Response & Threat Hunting with CHRYSALIS & DAISY by Jess Garcia

Robust and Equitable Uncertainty Estimation by Aaron Roth, PhD

AI-driven Healthcare Navigation by Kira Radinsky, PhD and Guy Elad

Orchestrating Data Assets instead of Tasks, with Dagster by Sandy Ryza

Tackling Climate Change with Machine Learning by Priya Donti, PhD

Riding the Tailwind of NLP Explosion by Rongyao Huang

Continual Learning: Build Sustainable AI Models in Production by Ke Ji

Vector Search - A gentle introduction by Zain Hasan

Human Factors of Explainable AI by Meg Kurdziolek, PhD

CI:CD for Machine Learning by Alex Kim

Cybersecurity and Policing in the Metaverse by Jack McCauley

Archetypal Analysis: Maintaining Contrastive Categories in Cluster Analysis by Jacob Nelson

Achieving Techquity_Digital Health Equity by Tushar Mehrotra and Michael Thompson

Cloud Directions, MLOps and Production Data Science by Joe Hellerstein, PhD

MySQL HeatWave ML – the Easiest, Fastest, and Least Expensive Way to Add Powerful Machine Learning Capabilities to your MySQL Applications ин Sandeep Agrawal, PhD and Salil Pradhan

Unleash your Neural Networks with Applied Explainability by Yotam Azriel

Real-time Analytics, AI&Apps with Deephaven Data Labs by Pete Goddard

Data Science Platforms are Bad by Hugo Shi

Turbo Boost Workflows for AI, ML, DevOps and EDA with Modern File Utilities by Keshav Attrey

HPCC Systems – The Kit and Kaboodle for Big Data and Data Science by Bob Foreman

Azure AI Powered Global Translator by Savita Mittal

Data Science at 200mph, How HP Data Science Powers Winning Racing, Presented by HP Inc by Alex Duncan and Steve Sutton

Unlocking High Quality Data with Ground Control by Lucas Chatham

Methods and Tools for Time Series Data Science Problems with InfluxDB by Zoe Steinkamp

Graph Data Science Framework for the Enterprise by Stuart Laurie

Unravel Data - Empowering DevOps for Data Teams by Keith Alsheimer and Chris Santiago

Any Way You Want It_ Integrating Complex Business Requirements into ML Forecasting Systems by David Koll

Making Data-driven Decisions with Azure Machine Learning & Responsible AI Dashboard by Manesh Raveendran Pillai

Big Data Analytics and Visualization with R by Ysis Wilson-Tarter

Transforming Enterprise Data Science with Transformers by Rajiv Shah, Ph

Perspectives on Hyperparameter Scheduling in Deep Learning by Cameron Wolfe

Lightning AI - Introduction to the PyTorch Lightning Ecosystem by Kaushik Bokka

West 2022 - Jennifer Dawn Davis - Domino Data Lab - Large Scale Deep Learning using the High-Performance Computing Library OpenMPI and DeepSpeed

Data Drift Identification for NLP Models in the Context of AI Governance for Enterprises by Sourav Mazumder

A Hands-on Introduction to Transfer Learning by Tamoghna Ghosh

NLP Fundamentals by Leonardo De Marchi and Laura Skylaki, PhD

Advanced Gradient Boosting: Probabilistic Regression and Categorical Structure by Brian Lucena

Deep Learning with Python and Keras (Tensorflow 2) by Amita Kapoor, PhD

Statistics for Data Science by Andrew Zirm, PhD

Introduction to Python for Data Analysis by Leonidas Souliotis, PhD

Introduction to Machine Learning by Julia Lintern

An Introduction to Data Literacy with SQL by Sheamus McGovern

Practical Tutorial on Uncertainty and Out-of-distribution Robustness in Deep Learning by Balaji Lakshminarayanan, PhD

Getting Started With Quantum Bayesian Networks in Python and Qiskit by Frank Zickert, PhD

AI4Cyber_ An Overview of the Field and an Open-Source Virtual Machine for Research and Education by Sagar Samtani, PhD

Colossal-AI_A Unified Deep Learning System For Large-Scale Parallel Training by James Demmel, PhD and Yang You, PhD

Practicing Trustworthy Machine Learning: A Tutorial by Subho Majumdar, PhD, Matthew McAteer, Yada Pruksachatkunv

Not Just Deep Fakes_Applications of Visual Generative Models in Pharma Manufacturing by Guglielmo Iozzia

Unifying ML With One Line of Code by Daniel Lenton, PhD

Full-stack Machine Learning for Data Scientists by Hugo Bowne-Anderson, PhD and Eddie Mattia

Foundations of Deep Reinforcement Learning by Pieter Abbeel, PhD

Machine Learning for the 99% by Giacomo Vianello