Ai+ Training

A Semi-Supervised Anomaly Detection System Through Ensemble Stacking Algorithm by Chuying Ma

The Crucial Role of Digital Experimentation and A/B Testing in the AI Landscape by Alessandro Romano

Causality and LLMs by Robert Osazuwa Ness, PhD

Connecting Large Language Models - Common Pitfalls & Challenges by Nils Reimers

Evaluating Synthetic Data with Post-Processing Techniques by Samruddhi (Sam) Kulkarni

Orchestrating Generative AI Workflows to Deliver Business Value by Hugo Bowne-Anderson, PhD

Finetuning, Serving, and Evaluating LLMs in the Wild by Hao Zhang, PhD

How to Systematically Evaluate and Improve your Generative AI Application by Beatriz Strollnitz and Daniel Schneider

Adversarial Validation and Training in Stock Market Price Prediction by Giacomo Maccagni and Federico Minutoli

Evaluating Recommendation Algorithms at Delivery Hero by Manchit Madan

Integrating Language Models for Automating Feature Engineering Ideation by Sergey Yurgenson

Towards Explainable and Language-Agnostic LLMs by Walid S. Saba

Adopting Language Models Requires Risk Management — This is How by Patrick Hall

Security First, Create a Robust Machine Learning Model by Teodora Sechkova

Representation Learning on Graphs and Networks by Dr. Petar Veličković

Building Robust and Scalable Recommendation Engines for Online Food Delivery by Raghav Bali and Vishal Natani

PyTorch 2.1 - New Developments by Supriya Rao

Generative Ai vs. AGI: Strengths and Weaknesses of Large Language Models by Dr. Ben Goertzel

The Ethics of Digital Minds: A baffling new frontier by Nick Bostrom, PhD

Ask the Experts! ML Pros Deep-Dive into Machine Learning Techniques and MLOps by Seth Juarez

LLMs in Data Analytics: Can They Match Human Precision? by Gerard Kostin

The Tangent Information Modeler, time series modeling reinvented by Philip Wauters