How to Implement an ML, XAI, and Transformer NLP model in an e-Business

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Topic: How to Implement an ML, XAI, and Transformer NLP model in an e-Business

Speaker: Denis Rothman, Artificial Intelligence Expert, Author, Instructor
https://www.linkedin.com/in/denis-rothman-0b034043/

Denis graduated from Sorbonne University and Paris-Diderot University. He wrote and registered a patent for one of the very first word2vector embeddings and word piece tokenization solutions 30+ years ago as a student and started a company to deploy AI. Denis went full speed from the start to - begin his career, authoring one of the first AI cognitive NLP chatbots applied as a language teacher for Moët et Chandon and other companies. -author an AI resource optimizer for IBM and apparel producers. -author an Advanced Planning and Scheduling (APS) solution used worldwide.
He rapidly became an expert in explainable AI (XAI) from the start to add interpretable mandatory, acceptance-based explanation data and explanation interfaces to the solutions implemented for major corporate aerospace, apparel, and supply chain projects.

Abstract:
This presentation will take you from theory to practice. It will show you how to implement AI when the mathematics of AI conflicts with the real world's physics: lack of data, lack of computer power, human expertise, and funding.

The presentation will illustrate real-time and delivery for millions of online consumers and thousands of targeted videos on streaming platforms such as Netflix, Amazon Prime, Disney+, and YouTube. This automated e-business system will collect consumer features in real-time and make highly efficient suggestions.

The presentation will explore an AI pipeline from A to Z with notebooks in Python, Pytorch, and the main frameworks.

The pipeline will begin by collecting consumer feature data with machine learning and deep learning algorithms such as a Restricted Boltzmann Machine(RBM). Explainable AI(XAI) will ensure that the dataset is ethical and legal using WIT, SHAP, and other XAI algorithms. Finally, the presentation will introduce the mind-blowing NLP Transformer models to predict consumer behavior and create automatic near-human real-time dialogs.

At the end of the presentation, you will fully understand the factors involved in a real-life implementation of artificial intelligence algorithms in a corporate pipeline with an unlimited number of users.

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