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.
What You'll Learn
Talks & Workshops on these topics:
Topics
Natural Language Processing
NLP Transformers
Pre-trained Models
Text Analytics
Natural Language Understanding
Sentiment Analysis
Natural Language Generation
Speech Recognition
Named Entity Extraction
Models
BERT
XLNet
GPT-2
Transformers
Word2Vec
Deep Learning Models
RNN & LSTM
Machine Learning Models
ULMFiT
Transfer Learning
Tools
Tensorflow 2.0
Hugging Face Transformers
PyTorch
Theano
SpaCy
NLTK
AllenNLP
Stanford CoreNLP
Keras
FLAIR
ODSC EUROPE Hybrid Conference 2024
Register your interest for 2024Past NLP Speakers
Piotr Mirowski, PhD
Dr. Piotr Mirowski is a Staff Research Scientist at DeepMind. His research on artificial intelligence covers the subjects of reinforcement learning, navigation, weather and climate forecasting, as well as a socio-technical systems approach to human-machine collaboration and to computational creativity. He is the author of over 60 papers that have been published in Nature, Genome Biology, Clinical Neurophysiology or at ICLR, AAAI and NeurIPS. Piotr studied computer science in France at ENSEEIHT Toulouse and obtained his PhD in computer science in 2011 at New York University, with a thesis supervised by Prof. Yann LeCun (Outstanding Dissertation Award, 2011). A trained actor himself, Piotr founded and directs Improbotics, a theatre company where human actors and robots improvise live comedy performances and investigate the use of AI for artistic human and machine-based co-creation. https://piotrmirowski.com
Dr. Gözde Gül Şahin
Dr. Gözde Gül Şahin is an Assistant Prof. at Koç University and a KUIS AI Fellow since February 2022. Previously, she was a postdoctoral researcher in the Ubiquitous Knowledge Processing (UKP) Lab at the Technical University of Darmstadt, Germany. Her research spans the fields of linguistics and machine learning, in particular semantics, multilingual representations and large language models. She completed her PhD studies in Istanbul Technical University (İTÜ) Computer Engineering department in 2018. She was a visiting researcher at the Institute for Language, Cognition and Computation (ILCC) of the University of Edinburgh in 2017. Before her Ph.D., she received her Masters and Bachelor degrees from Sabancı University in 2011 and İTÜ in 2009, respectively. She regularly serves as a PC member for *ACL conferences and is a co-organizer for the Workshop on Multilingual Representation Learning (MRL). Her research on NLP has been funded by Tübitak 2232, and 2236 grant programs that are granted to outstanding young principal investigators.
Semantic Analysis and Procedural Language Understanding in the Era of Large Language Models(Talk)
Leonardo De Marchi
Leonardo De Marchi holds a Master in Artificial intelligence and has worked as a Data Scientist in the sports world, with clients such as the New York Knicks. He now works in Thomson Reuters as VP of Labs, and also provides consultancy and training for small and large companies. His previous experience includes being Head of Data Science and Analytics in Bumble, the largest dating site with over 500 million users, heading the team through acquisition and an IPO.
Laura Skylaki, PhD
Laura Skylaki is a Manager of Applied Research in Thomson Reuters Labs, where she leads advanced machine learning projects in the domain of Legal and Tax AI.With a career spanning more than a decade at the intersection of research and practical application, she has contributed technical expertise in diverse fields such as bioinformatics and stem cell biology, image processing and natural language processing. She holds a doctorate in stem cell bioinformatics from the University of Edinburgh, UK, and has been publishing on machine learning applications in leading academic journals since 2012.
NLP Fundamentals(Training)
Julien Simon
Julien is currently Chief Evangelist at Hugging Face. He’s recently spent 6 years at Amazon Web Services where he was the Global Technical Evangelist for AI & Machine Learning. Prior to joining AWS, Julien served for 10 years as CTO/VP Engineering in large-scale startups.
Hyper-productive NLP with Hugging Face Transformers(Workshop)
Daniel Whitenack, PhD
Daniel Whitenack (aka Data Dan) is a Ph.D. trained data scientist working with SIL International on NLP and speech technology for local languages in emerging markets. He has more than ten years of experience developing and deploying machine learning systems at scale. Daniel co-hosts the Practical AI podcast, has spoken at conferences around the world (Applied Machine Learning Days, O’Reilly AI, QCon AI, GopherCon, KubeCon, and more), and occasionally teaches data science/analytics at Purdue University.
Modern NLP: Pre-training, Fine-tuning, Prompt Engineering, and Human Feedback(Workshop)
Sofie Van Landeghem, PhD
Sofie is a machine learning and NLP engineer who firmly believes in the power of data to transform decision making in industry. She has a Master in Computer Science (software engineering) and a PhD in Sciences (Bioinformatics), and more than 16 years of experience in Natural Language Processing and Machine Learning, including in the pharmaceutical industry and the food industry. In 2019, she joined Explosion to work on the open-source NLP library spaCy. She is currently leading the open-source team developing and maintaining spaCy, as well as various other open-source developer tools for data scientists.
spaCy: a customizable NLP toolkit designed for developers(Talk)
Christian Ramirez
Christian is Machine Learning Technical Leader at Mercado Libre, the largest e-commerce/fintech company in Latin America, where he dedicates his efforts to creating tools for monitoring and quality of learning models. He is a Computer Engineer and Master in Science with a major in Astronomy from UNAM (Universidad Nacional Autonoma de Mexico). He is a “Xoogler” and has more than 15 years of experience in the field of machine learning. He has lectured in almost a dozen countries.
Introduction to Topological Data Analysis Workshop(Tutorial)
Sophia Ananiadou
Sophia Ananiadou is Professor in Computer Science, Department of Computer Science, the University of Manchester. She is also Director of the National Centre for Text Mining (NaCTeM)); Deputy Director of the University’s Institute of Data Science and AI (IDSAI); Distinguished Research Fellow at the AI Research Centre of the National Institute of Advanced Industrial Science and Technology, Japan; Alan Turing Institute Fellow; Honorary Professor, University of the Aegean and Member of European Laboratory for Learning and Intelligent Systems Society. Her research interests evolved from abstract work on fragments of linguistic theory and logic to exploration of how AI systems could acquire and exploit knowledge of language, particularly in specialised domains (biomedicine, chemistry, exposome, law, public health). Research contributions include neural information extraction, text summarisation and simplification, emotion detection, terminology, development of resources (lexica, terminologies and labelled data), annotation tools and interoperable platforms for NLP workflows. She has developed tools such as the RobotAnalyst to improve evidence-based decisions, cut costs and improve efficiency and robustness of key policy decisions in public health.
Avik Sengupta
Avik Sengupta is the head of product development and software engineering at Julia Computing, contributor to open source Julia and maintainer of several Julia packages. Avik is the author of Julia High Performance, co-founder of two artificial intelligence start-ups in the financial services sector and creator of large complex trading systems for the world’s leading investment banks.
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
Who will attend
Some of the world’s best data science speakers
The brains and authors behind today’s most popular open data science tools, topics, and languages
Hundreds of attendees focused on data science
Chief Data Scientists
Thought leaders working in data science
Data Scientists and Analysts
Software Developers
CEOs, CTOs, CIOs
Data Visualization professionals
Venture Capitalists and Investors
Startup Founders and Executives
Attendees from Healthcare, Finance, Education, Business, Intelligence, and other industries
Big data and data science innovators
ODSC EUROPE Hybrid Conference 2024
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