A step-by-step guide to build machine learning and NLP models using Google AutoML KEY FEATURESÊ ¥Understand the basic concepts of Machine Learning and Natural Language Processing ¥Understand the basic concepts of Google AutoML, AI Platform, and Tensorflow ¥Explore the Google AutoML Natural Language service ¥Understand how to implement NLP models like Issue Categorization Systems using AutoML ¥Understand how to release the features of AutoML models as REST APIs for other applications ¥Understand how to implement the NLP models using the Google AI Platform DESCRIPTIONÊÊ Google AutoML and AI Platform provide an innovative way to build an AI-based system with less effort. In this book, you will learn about the basic concepts of Machine Learning and Natural Language Processing. You will also learn about the Google AI services such as AutoML, AI Platform, and Tensorflow, GoogleÕs deep learning library, along with some practical examples using these services in real-life scenarios. You will also learn how the AutoML Natural Language service and AI Platform can be used to build NLP and Machine Learning models and how their features can be released as REST APIs for other applications. In this book, you will also learn the usage of GoogleÕs BigQuery, DataPrep, and DataProc for building an end-to-end machine learning pipeline. Ê This book will give you an in-depth knowledge of Google AutoML and AI Platform by implementing real-life examples such as the Issue Categorization System, Sentiment Analysis, and Loan Default Prediction System. This book is relevant to the developers, cloud enthusiasts, and cloud architects at the beginner and intermediate levels. WHAT YOU WILL LEARNÊ By the end of this book, you will learn how Google AutoML, AI Platform, BigQuery, DataPrep, and Dapaproc can be used to build an end-to-end machine learning pipeline. You will also learn how different types of AI problems can be solved using these Google AI services. A step-by-step implementation of some common NLP problems such as the Issue Categorization System and Sentiment Analysis System that provide you with hands-on experience in building complex AI-based systems by easily leveraging the GCP AI services. Ê WHO IS THIS BOOK FORÊ This book is for machine learning engineers, NLP users, and data professionals who want to develop and streamline their ML models and put them into production using Google AI services. Prior knowledge of python programming and the basics of machine learning would be preferred. TABLE OF CONTENTS 1. Introduction to Artificial Intelligence 2. Introducing the Google Cloud Platform 3. AutoML Natural Language 4. Google AI Platform 5. Google Data Analysis, Preparation, and Processing Services AUTHOR BIOÊ Navin Sabharwal: Navin is an innovator, leader, author, and consultant in AI and Machine Learning, Cloud Computing, Big Data Analytics, Software Product Development, Engineering, and R&D. He has authored books on technologies such as GCP, AWS, Azure, AI and Machine Learning systems, IBM Watson, chef, GKE, Containers, and Microservices. He is reachable at Navinsabharwal@gmail.com. Amit Agrawal: Amit holds a masterÕs degree in Computer Science and Engineering from MNNIT (Motilal Nehru National Institute of Technology, Allahabad), one of the premier institutes of Engineering in India. He is working as a principal Data Scientist and researcher, delivering solutions in the fields of AI and Machine Learning. He is responsible for designing end-to-end solutions and architecture for enterprise products. He is reachable at agrawal.amit24@gmail.com.
This book covers concepts and the latest developments on microscale flow and heat transfer phenomena involving a gas. The book is organised in two parts: the first part focuses on the fluid flow and heat transfer characteristics of gaseous slip flows. The second part presents modelling of such flows using higher-order continuum transport equations. The Navier-Stokes equations based solution is provided to various problems in the slip regime. Several interesting characteristics of slip flows along with useful empirical correlations are documented in the first part of the book. The examples bring out the failure of the conventional equations to adequately describe various phenomena at the microscale. Thereby the readers are introduced to higher order continuum transport (Burnett and Grad) equations, which can potentially overcome these limitations. A clear and easy to follow step by step derivation of the Burnett and Grad equations (superset of the Navier-Stokes equations) is provided in the second part of the book. Analytical solution of these equations, the latest developments in the field, along with scope for future work in this area are also brought out. Presents characteristics of flow in the slip and transition regimes for a clear understanding of microscale flow problems; Provides a derivation of Navier-Stokes equations from microscopic viewpoint; Features a clear and easy to follow step-by-step approach to derive Burnett and Grad equations; Describes a complete compilation of few known exact solutions of the Burnett and Grad equations, along with a discussion of the solution aided with plots; Introduces the variants of the Navier-Stokes, Burnett and Grad equations, including the recently proposed Onsager-Burnett and O13 moment equations.
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 owncognitive 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.
· 2016
The life of an individual is nearly about eight to ninety years in which we have hundreds of months, thousands of weeks, thousands of days, and around millions of hours, and every hour, we perform many activities. Every activity generates some thoughts in our mind and these are the thoughts that mainly shape our personality and influence our future working. Our daily interaction in many work areas with both living and nonliving things is basically a driver of our thought generation process. Through this, we develop our personality, and we work accordingly. Everyone in this world has grown with different surroundings, and different surrounding is having different living and nonliving things and if all human beings are grown up having different surroundings then all are also having different personality because everyone, after all, learns from his surrounding only. A baby born in an English-speaking family always speak English when he starts speaking , and a baby born in a Hindi-speaking family will always speak Hindi. This is because they learn these things from their surroundings. It is your surroundings that totally dominate your thoughts in day-to-day life, and you take decision as per that. In dominance of those surroundings, some make good decisions and some make bad decisions. Persons taking good decision are successful, and persons taking bad decision are not successful. This book navigates through all such personality traits, which human possess. Books let you understand those personality traits in various situation, surroundings, and thoughts, which are main driver of human beings success.
· 2020
El aprendizaje de la neuroanatomía es un reto. En esta obra hemos construido un sencillo texto que nace del interés del estudiante de medicina para comprender el mundo de la neuroanatomía. Sencillo, pero no simple, esa es nuestra perspectiva de la neuroanatomía. Este libro brinda elementos fundamentales para el aprendizaje de conceptos neuroanatómicos. La lectura de este texto contribuirá a enriquecer nuestros conocimientos del sistema nervioso de manera amena.
· 2020
Aneurysmal subarachnoid Hemorrhage (SAH) is one of the major intracranial calamities that an individual can suffer from and which the doctor may face. It is defined as the blood into the subarachnoid space, where cerebrospinal fluid (CSF) normally circulates, or when an intracranial hemorrhage extends to that space. The aneurysmal rupture leads the patient to a critical state, with a high probability of morbidity and mortality. The care and management of patients with subarachnoid hemorrhage is vital for satisfactory evolution, as is the multidisciplinary approach involving endovascular neurosurgeons and neurosurgeons with experience in microsurgical management of cerebral aneurysms. Supported by Asociación Ayuda Enfermo Neuroquirúrgico (AAEN).
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· 2022
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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. You will: 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.