Natural Language Processing: The Trends Shaping Adoption in 2021

Adoption, investment, and budgets are increasing

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A few Natural Language Processing tools stand out in particular

Accuracy remains a top priority

People still have questions about

Conclusion on Natural Language Processing Trends

  • Transferable Representation in Natural Language Processing: Kai-Wei Chang, PhD | Director/Assistant Professor | UCLA NLP/UCLA CS
  • Build a Question Answering System using DistilBERT in Python: Jayeeta Putatunda | Data Scientist | MediaMath
  • Introduction to NLP and Topic Modeling: Zhenya Antić, PhD | NLP Consultant/Founder | Practical Linguistics Inc
  • NLP Fundamentals: Leonardo De Marchi | Lead Instructor | ideai.io
  • GANs: Theory and Practice, Image Synthesis With GANs Using TensorFlow: Ajay Baranwal | Center Director | Center for Deep Learning in Electronic Manufacturing, Inc
  • Machine Learning With Graphs: Going Beyond Tabular Data: Dr. Clair J. Sullivan | Data Science Advocate | Neo4j
  • Deep Dive into Reinforcement Learning with PPO using TF-Agents & TensorFlow 2.0: Oliver Zeigermann | Software Developer | embarc Software Consulting GmbH
  • Get Started with Time-Series Forecasting using the Google Cloud AI Platform: Karl Weinmeister | Developer Relations Engineering Manager | Google
  • Towards More Energy-Efficient Neural Networks? Use Your Brain!: Olaf de Leeuw | Data Scientist | Dataworkz
  • Practical MLOps: Automation Journey: Evgenii Vinogradov, PhD | Head of DHW Development | YooMoney
  • Applications of Modern Survival Modeling with Python: Brian Kent, PhD | Data Scientist | Founder The Crosstab Kite
  • Using Change Detection Algorithms for Detecting Anomalous Behavior in Large Systems: Veena Mendiratta, PhD | Adjunct Faculty, Network Reliability, and Analytics Researcher | Northwestern University

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