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< div="" style=""> This book comprises select proceedings of
the 46th National Conference on Fluid Mechanics and Fluid Power
(FMFP 2019). The contents of this book focus on aerodynamics and
flow control, computational fluid dynamics, fluid structure
interaction, noise and aero-acoustics, unsteady and pulsating
flows, vortex dynamics, nuclear thermal hydraulics, heat transfer
in nanofluids, etc. This book serves as a useful reference
beneficial to researchers, academicians and students interested in
the broad field of mechanics. ^
Get hands-on knowledge of how BERT (Bidirectional Encoder
Representations from Transformers) can be used to develop question
answering (QA) systems by using natural language processing (NLP)
and deep learning. The book begins with an overview of the
technology landscape behind BERT. It takes you through the basics
of NLP, including natural language understanding with tokenization,
stemming, and lemmatization, and bag of words. Next, you'll look at
neural networks for NLP starting with its variants such as
recurrent neural networks, encoders and decoders, bi-directional
encoders and decoders, and transformer models. Along the way,
you'll cover word embedding and their types along with the basics
of BERT. After this solid foundation, you'll be ready to take a
deep dive into BERT algorithms such as masked language models and
next sentence prediction. You'll see different BERT variations
followed by a hands-on example of a question answering system.
Hands-on Question Answering Systems with BERT is a good starting
point for developers and data scientists who want to develop and
design NLP systems using BERT. It provides step-by-step guidance
for using BERT. What You Will Learn Examine the fundamentals of
word embeddings Apply neural networks and BERT for various NLP
tasks Develop a question-answering system from scratch Train
question-answering systems for your own data Who This Book Is For
AI and machine learning developers and natural language processing
developers.
Follow a step-by-step, hands-on approach to building
production-ready enterprise cognitive virtual assistants using
Google Dialogflow. This book provides an overview of the various
cognitive technology choices available and takes a deep dive into
cognitive virtual agents for handling complex real-life use cases
in various industries such as travel and weather. You'll delve
deeper into the advanced features of cognitive virtual assistants
implementing features such as input/output context, follow-up
intents, actions and parameters, and handling complex multiple
intents. You'll learn how to integrate with third-party messaging
platforms by integrating your cognitive bot with Facebook
messenger. You'll also integrate with third-party APIs to enrich
your cognitive bots using webhooks. Cognitive Virtual Assistants
Using Google Dialogflow takes the complexity out of the cognitive
platform and provides rich guidance which you can use when
developing your own cognitive bots. The book covers Google
Dialogflow in-depth and starts with the basics, serving as a
hands-on guide for developers who are starting out on their journey
with Google Dialogflow. All the code presented in the book will be
available in the form of scripts and configuration files, which
allows you to try out the examples and extend them in interesting
ways. What You Will Learn Develop cognitive bots with Google
Dialogflow technology Use advanced features to handle complex
conversation scenarios Enrich the bot's conversations by
understanding the sentiment of the user See best practices for
developing cognitive bots Enhance a cognitive bot by integrating
with third-party services Who This Book Is For AI and ML
developers.
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