March 30th – April 1st, 2021
Natural Language Processing Track
Learn the latest models, advancements, and trends from the top practitioners and researchers behind NLP
NLP has seen rapid advances in recent years. With some of the sharpest minds in data science presenting, get the latest insights, natural language processing training, trends, and discoveries in data science languages, tools, topics – and beyond.
Connect with some of the most innovative people and ideas in the world of data science, while learning first-hand from core practitioners and contributors. Learn about the latest advancements and trends in NLP, including pre-trained models, with use-cases focusing on deep learning, speech-to text, and semantic search.
Some of Our Current NLP Speakers

Julia Neagu, PhD
Julia is the Director of Analytics at Tamr, where she is expanding the company’s analytics and data science solutions. Before joining Tamr, she led end-to-end modeling and development of data science products at Aon’s Intellectual Property Solutions group. Her previous experience includes technology-focused litigation consulting, quantitative finance, and private equity. Julia has a PhD in Physics from Harvard.
The Healthy Approach – Organic Data Enrichment Through Entity Extraction(Talk)

Ian Bakst, PhD
Ian is a DataOps Engineer at Tamr, where he works on designing and implementing Tamr’s data solutions for clients. Before Tamr, Ian applied machine learning models to research properties of materials. His previous work includes high-throughput modeling of superelasticity in a novel class of intermetallic crystals. Ian has a PhD in Mechanical Engineering from Colorado State University.
The Healthy Approach – Organic Data Enrichment Through Entity Extraction(Talk)

Elliott Ning
Elliott Ning is a passionate technology advisor of Google for data analytics, infrastructure modernization, and AI to bring organizations business opportunities into reality. Previously he has worked in leading technology companies including Oracle and Huawei to transform enterprises by developing solutions and strategies on cloud platforms and data centers. Elliott holds two MS degrees in Software Engineering and Manufacturing Management, and extensive industrial certifications in IT and cloud.
Accelerating The Journey To Document Understanding AI(Tutorial)
Some of Our Previous NLP Speakers

Thomas Wolf, PhD
Thomas leads the Science Team at Huggingface Inc., a Brooklyn-based startup working on Natural Language Generation and Natural Language Understanding.
After graduating from Ecole Polytechnique (Paris, France), he worked on laser-plasma interactions at the BELLA Center of the Lawrence Berkeley National Laboratory (Berkeley, CA). Got accepted for a PhD at MIT (Cambridge, MA) but ended up doing his PhD in Statistical/Quantum physics at Sorbonne University and ESPCI (Paris, France), working on superconducting materials for the French DARPA (DGA) and Thales.
Thomas is interested in Natural Language Processing, Deep Learning, and Computational Linguistics. Much of his research is about Natural Language Generation (mostly) and Natural Language Understanding (as a tool for better generation).
An Introduction to Transfer Learning in NLP and HuggingFace Tools(Workshop)

Kimberly Fessel, PhD
Kimberly Fessel is a Senior Data Scientist at Metis, the industry’s only accredited, full-time, immersive data science bootcamp. Prior to joining Metis as an instructor, Kimberly worked in digital advertising at MRM//McCann where she focused on helping clients understand their customers by leveraging unstructured data with modern NLP techniques. She holds a Ph.D. in applied mathematics from Rensselaer Polytechnic Institute and completed an NSF-funded postdoctoral fellowship in math biology at the Ohio State University. She is passionate about data visualization and about harnessing the power of language to tell compelling data stories.

Joan Xiao, PhD
Joan Xiao is a Principal Data Scientist at Linc Global, a commerce-specialized customer care automation company. In her role, she applies novel natural language processing and machine learning techniques to improve customer experience. Previously she led machine learning and data science teams at various companies ranging from startup to Fortune 100. Joan received her Ph.D in Mathematics and MS in Computer Science from University of Pennsylvania.
Transfer Learning in NLP(Talk)

Dr. Anju Kambadur
Dr. Prabhanjan (Anju) Kambadur heads the AI Engineering group at Bloomberg. Anju leads a group of 100+ researchers and engineers who build solutions for Bloomberg clients in the areas of machine learning, natural language processing (NLP) and natural language understanding, information extraction, knowledge graphs, question answering, and table understanding. Previously, Anju was a research staff member in the Business Analytics and Mathematical Sciences Department at IBM Research’s Thomas J. Watson Research Center, where he worked on problems in machine learning, such as matrix sketching, genome-wide association studies, temporal causal modeling, and high-performance computing. He received his PhD from Indiana University. Anju has published peer-reviewed articles in the fields of high-performance computing, machine learning, and natural language processing.
AI Research at Bloomberg(Talk)
See all our talks and hands-on workshop and training sessions
See all sessionsWhat You'll Learn
Talks & Workshops on these topics:
Topics
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Natural Language Processing
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NLP Transformers
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Pre-trained Models
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Text Analytics
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Natural Language Understanding
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Sentiment Analysis
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Natural Language Generation
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Speech Recognition
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Named Entity Extraction
Models
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BERT
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XLNet
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GPT-2
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Transformers
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Word2Vec
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Deep Learning Models
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RNN & LSTM
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Machine Learning Models
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ULMFiT
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Transfer Learning
ToolsÂ
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Tensorflow 2.0
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Hugging Face Transformers
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PyTorch
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TheanoÂ
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SpaCy
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NLTK
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AllenNLP
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Stanford CoreNLP
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Keras
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FLAIRÂ
You Will Meet
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Some of the world’s best data science speakers
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The brains and authors behind today’s most popular open data science tools, topics, and languages
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Hundreds of attendees focused on data science
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Chief Data Scientists
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Thought leaders working in data science
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Data Scientists and Analysts
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Software Developers
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CEOs, CTOs, CIOs
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Data Visualization professionals
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Venture Capitalists and Investors
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Startup Founders and Executives
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Attendees from Healthcare, Finance, Education, Business, Intelligence, and other industries
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Big data and data science innovators
Why Attend?
Several of the best minds and biggest names in data science will be presenting
Network with attendees from leading data science companies to learn how others are tackling similar problems
Gain quality training in the hottest data science topics, tools, and languages
Learn the latest in data science from industry leaders without having to make room in the budget — tickets are surprisingly inexpensive