What is this video about, and why is it important?
Natural language processing (NLP) involves the application of machine learning and other statistical techniques to derive insights from language. As the volume of text-based data, such as documents, tweets, and email, continues to grow, techniques in natural language processing are becoming central to modern intelligent applications.
This video will bring you up-to-speed on the state of NLP, and explore current approaches to integrate AI and deep learning at scale for NLP. You’ll learn strategies for moving from proof of concept to a full-scale product, understand key techniques in NLP, and learn how to integrate these techniques based on the goals for your business.
In this series of five curated talks from O’Reilly’s Artificial Intelligence Conference in New York, June 2017, you'll join a group of experts in the field of AI to discover deep learning breakthroughs for conversational AI, understand the technologies involved with this emerging field, and learn what is possible with current NLP techniques.
What you’ll learn—and how you can apply it
- Explore the current landscape relating to natural language understanding in the enterprise, including bots, natural language processing, and text generation
- Understand the challenges of and techniques for scaling up NLP in the enterprise
- Learn about recent deep learning breakthroughs for conversational AI, and how they can be utilized in practice
- Understand the research underpinning AI products and services powered by language understanding
- Learn about current approaches in reading comprehension, and how they can be used as a benchmark for evaluating NLP systems
- Gain a broad understanding of techniques in advanced natural language generation, options for related technologies, and how to choose the best options for your business goals
- Discover examples of the practical applications of artificial intelligence in the context of machine reading and writing, including questioning, answering, and decision making
- Explore key research areas and learn how they will power new products and services in language understanding
- Understand the current state of the art in NLP
- Identify traditional versus new deep learning-based approaches to NLP, and understand when to utilize each approach
This video is for you because…
- You are a data scientist who needs to process natural language data, and you are interested in moving from traditional to deep learning-based techniques
- You are a manager or executive working in an organization that needs to process language-based data, and you want to understand the latest options, technologies, and best practices for utilizing text data to improve your products or services
- A general understanding of basic concepts related to NLP, machine learning, and deep learning is useful but not required
- An understanding of how your business goals relate to your organization’s text-based data
Materials or downloads needed in advance: None.
Table of contents
- Beyond the state of the art in reading comprehension - Jennifer Chu-Carroll (Elemental Cognition)
- What, how, and why: The dynamic of advanced NLG - Kristian Hammond (Narrative Science)
- Conversational AI at large scale - Yishay Carmiel (Spoken Communications)
- Bigger than bots: Machine reading and writing in enterprise - Mohamed Musbah (Maluuba Inc.)
- Adding meaning to natural language processing - Jonathan Mugan (DeepGrammar)
- Title: AI and Deep Learning for NLP: Tools and Techniques for the Enterprise
- Release date: August 2017
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781491998298
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