Ai+ Training

MLOps in the Enterprise by Abe Omorogbe

A bamboo of Pandas: crossing Pandas' single-machine barrier with Apache Spark by Itai Yaffe Daniel Haviv

The Power Of Hexagons: How H3 & Foursquare Are Transforming Spatial Analytics by Nick Rabinowitz

What I love and hate about Dask by Matthew Rocklin, PhD

Responsible AI for Customer Product Organizations by Aishwarya Srinivasan

Need of Adaptive Ethical ML Models in Post Pandemic Era by Sharmistha Chatterjee and Juhi Pandey

MLOps: Relieving Technical Debt in ML with MLflow, Delta and Databricks by Sean Owen Yinxi Zhang, PhD

What do lawyers need (and want) from Legaltech? by Dr Felicity Bell

Security Operations for Machine Learning at Scale with MLSecOps by Alejandro Saucedo

Emotion Detection with Natural Language Inference by Serdar Cellat, PhD

Open-source Best Practices in Responsible AI by Violeta Misheva, PhD Daniel Vale

Human-Friendly, Production-Ready Data Science with Metaflow by Ville Tuulos

Drift Detection in Structured and Unstructured Data by Keegan Hines, PhD

Learned Optimizers: Learning to Learn Optimization Algorithms by Luke Metz

Unsolved ML Safety Problems Dan Hendrycks

Can We Let AI be Great? Practical Considerations in Designing Effective and Ethical AI Products. by Masheika Allgood

Timing IoT Devices to Slash Carbon Emissions at Scale by Gavin McCormick

Trustworthy AI by Jeannette M. Wing, PhD

WeightWatcher, an Open-Source Diagnostic Tool for Analyzing Deep Neural Nets by Michael Mahoney, PhD

The Origins, Purpose, and Practice of Data Observability by Kevin Hu

Best Practices for Data Annotation at Scale by Jai Natarajan

Tower of Babel: Making Apache Spark, Apache Mahout, Kubeflow, and Kubernetes Play Nice by Trevor Grant

Methods and Tools for Time Series Data Science Problems with InfluxDB, an Open-Source Time Series Database by Anais Dotis-Georgiou

How to Supercharge Spark with Apache Iceberg by Ryan Blue

Data Science Innovation with Z by HP Workstations and Software Stack by Bradley Franko Hunter Kempf

Simplifying MLOps by Taking Storage Worries out of the Equation by Miroslav Klivansky

AI for Clinical Care Planning and Decision Support by Sadid Hasan, PhD

Using AI for Immunogenicity Potential Assessment in Drug Discovery by Jiayi Cox, PhD

Natural Language Processing in Accelerating Business Growth by Sameer Maskey, PhD

Machine Learning for A/B Testing by Alex Peysakhovich, PhD

Kubernetes - Observability Engineering by Ravi Kumar Buragapu

Understanding and Optimizing Parallelism in NumPy-based Programs by Ralf Gommers, PhD

Gym and the Future of Reinforcement Learning by J K Terry

Data Science in the Cloud-Native Era by Yuan Tang

What We’ve Learned Pushing Nearly 100M Hours of GPU Compute by James Skelton

ImageNet and its Discontents. The Case for Responsible Interpretation in ML by Razvan Amironesei, PhD

Evaluating, Interpreting and Monitoring Machine Learning Models by Ankur Taly, PhD

Scaling AI Workloads with the Ray Ecosystem by Robert Nishihara

A New Indexing Technique for Quickly Fuzzy-Matching Entire Dataset Records by Dan S. Camper

Z by HP Panel Discussion on the Diverse Role of Data Science in Education by Max Urbany, Dan Chaney, Kristin Hempstead

Run Azure Machine Learning Anywhere in Multi-cloud or on Premises by Doris Zhong

Supercharging Geospatial Analysis In Your Data Science Workflow by Shan He

Building Provenance and Reproducibility into ML Systems by Adam Pocock, PhD

A New Data Format to Deliver Real-Time Data at Massive Scale by Denis Coady

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

The Hidden Layers of Tech Behind Successful Data Labeling by Glen Ford

Supercharging MLOps with Composability, Automation, and Scalability by Aurick Qiao, PhD, Tong Wen, PhD

Introduction to WSL2 for Data Science with Z by HP by Akram Dweikat

MLOps: From 0-60 with Pachyderm by Jimmy Whitaker

What to Do When Your Data Gets Big by Nathan Ballou

InfluxDB: The Database for Your Time Series Data Science Problems by Anais Dotis-Georgiou

Data Observability in 10 Minutes by Kevin Hu

Reimagine Clinical Research with the Power of Artificial Intelligence by Sanjay Patil

Accelerating MLOps with Kubernetes, CI/CD & GitOps by Audrey Reznik

Object detection with Red Hat OpenShift Data Science by Audrey Reznik Prasanth Anbalagan

Analyzing Sensitive Data Using Differential Privacy by Ashwin Machanavajjhala, PhD and Michael Hay, PhD

Vector Database Workshop Using Weaviate by Laura Ham

Text Categorization and Topic Modeling by Sanghamitra Deb, PhD

Towards Data Scientist - Friendly Natural Language Processing by Sepideh Seifzadeh and Monireh Ebrahimi

Prepare Data Science/ML Pipelines with Ease, Speed Following Best Practices by Ido Michael

A Tutorial on Contemporary Machine Learning Risk Management by Patrick Hall

Building and Deploying the World's Largest Rock/Paper/Scissors Competitive Ladder App in X Minutes with Roboflow and Streamlit by Jay Lowe

Tired of Cleaning your Data? Have Confidence in Data with Feature Types by John Peach

Streamlit: Next-generation Communication of Data Insights by Adrien Treuille, Phd

Full-stack Machine Learning for Data Scientists by Hugo Bowne-Anderson

Open-source Tools for Synthetic Data On-Demand by Lipika Ramaswamy

Deep Dive Workshop for Apache Superset by Srinivasa Kadamati

Quantization in PyTorch by Jerry Zhang

Bridging the Gap Between Data Scientists and Business Users by Amir Meimand, PhD

Overview of methods to handle missing values by Julie Josse, PhD Gael Varoquaux, PhD

Machine Learning for Causal Inference by Stefan Wager, PhD

Creating and Operating ML Models from Event-based Data Using Feature Stores and Feature Engines by Dr. Charna Parkey

Overview of Geocomputing and GeoAI at Oak Ridge National Laboratory: Exploitation at Scale, Anytime, Anywhere by Dalton Lunga, PhD, Jacob Arndt, Jesse Piburn

The Future of Software Development Using Machine Programming by Justin Gottschlich, Ph.D.

Hands-on Reinforcement Learning with Ray and RLlib by Richard Liaw, PhD, Christy Bergman, Avnish Narayan

Evolution of NLP and its Underpinnings by Chengyin Eng

Few-Shot Learning by Isha Chaturvedi

Telling stories with data by Gulrez Khan

Self-supervised Representation Learning for Speech Processing by Abdel-rahman Mohamed, PhD

Self-Supervised and Unsupervised Learning for Conversational AI and NLP by Chandra Khatri

NLP Fundamentals by Leonardo de Marchi

Transformers & Datasets for Research and Production by Patrick von Platen

SQL for Data Science by Mona Khalil

Manipulating and Visualizing Data with R by Jared Lander

Programming with Data: Python and Pandas by Daniel Gerlanc

Introduction to Scikit-learn: Machine Learning in Python by Thomas Fan

Intermediate Machine Learning with Scikit-learn: Cross-validation, Parameter Tuning, Pandas Interoperability, and Missing Values by Thomas Fan

Painting with Data: Introduction to d3.js by Ian Johnson

Transformer Based Approaches to Named Entity Recognition (NER) and Relationship Extraction (RE) by Sujit Pal

Advanced Machine Learning with Scikit-learn: Text Data, Imbalanced Data, and Poisson Regression by Thomas Fan

Tutorial: Building and Deploying Machine Learning Models with TensorFlow and Keras by Yong Tang, PhD

Introduction to the PyTorch Lightning Ecosystem by Kaushik Bokka Jirka Borovec, PhD

Intermediate Machine Learning with Scikit-learn: Evaluation, Calibration, and Inspection by Thomas Fan

AI Investors Reverse Pitch by Igor Taber, Sarah Fay, Danel Dayan

Women in Data Science Ignite by by Sewalita Duara, Amy E. Holder, Ahn Tran Reshmi Ghosh