Welcome to our book review site go-pdf.online!
You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
Practical Natural Language Processing
Many books and courses tackle natural language processing (NLP) problems with toy use cases and well-defined datasets. But if you want to build, iterate, and scale NLP systems in a business setting and tailor them for particular industry verticals, this is your guide. Software engineers and data scientists will learn how to navigate the maze of options available at each step of the journey. Through the course of the book, authors Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, and Harshit Surana will guide you through the process of building real-world NLP solutions embedded in larger product setups. You’ll learn how to adapt your solutions for different industry verticals such as health...
Practical Natural Language Processing
Many books and courses tackle natural language processing (NLP) problems with toy use cases and well-defined datasets. But if you want to build, iterate, and scale NLP systems in a business setting and tailor them for particular industry verticals, this is your guide. Software engineers and data scientists will learn how to navigate the maze of options available at each step of the journey. Through the course of the book, authors Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, and Harshit Surana will guide you through the process of building real-world NLP solutions embedded in larger product setups. You’ll learn how to adapt your solutions for different industry verticals such as health...
Blueprints for Text Analytics Using Python
Turning text into valuable information is essential for businesses looking to gain a competitive advantage. With recent improvements in natural language processing (NLP), users now have many options for solving complex challenges. But it's not always clear which NLP tools or libraries would work for a business's needs, or which techniques you should use and in what order. This practical book provides data scientists and developers with blueprints for best practice solutions to common tasks in text analytics and natural language processing. Authors Jens Albrecht, Sidharth Ramachandran, and Christian Winkler provide real-world case studies and detailed code examples in Python to help you get started quickly. Extract data from APIs and web pages Prepare textual data for statistical analysis and machine learning Use machine learning for classification, topic modeling, and summarization Explain AI models and classification results Explore and visualize semantic similarities with word embeddings Identify customer sentiment in product reviews Create a knowledge graph based on named entities and their relations
Machine Learning Interviews
As tech products become more prevalent today, the demand for machine learning professionals continues to grow. But the responsibilities and skill sets required of ML professionals still vary drastically from company to company, making the interview process difficult to predict. In this guide, data science leader Susan Shu Chang shows you how to tackle the ML hiring process. Having served as principal data scientist in several companies, Chang has considerable experience as both ML interviewer and interviewee. She'll take you through the highly selective recruitment process by sharing hard-won lessons she learned along the way. You'll quickly understand how to successfully navigate your way t...
Quakes that Rebuilt my life
Set in the twenty-first century, the modern era, where most people are busy with their daily chores and gadgets, and hardly have any time for self-realization, this story is based on a similar young character. He was different in the sense that he was aware of this problem. The real story, describes how he underwent a sudden change in his thought process after the quakes of November 12th, 2013. The new thought process, which made his life simpler, brought with it plenty of happiness. The happiness ignited in him a strange desire to write a book. In the book, he mentions descriptions of some of his ‘post-quake’ days, the negativities and dilemmas which he occasionally faced as a teenager, how he overcame them and how the quakes changed his perspective towards life. He illustrates how introspection can bring a beautiful change in life. But excess of anything is bad – this holds true for happiness too. It created a new dilemma for him: Was it some enlightenment, or was it insanity?
Natural Language Annotation for Machine Learning
Includes bibliographical references (p. 305-315) and index.
Big Data Analytics for Business Intelligence
To introduce the concepts of Big data Analytics for business intelligence and predictive modeling for SMART tourism product design in the Indian tourism industry. Quantitative literature survey of the contemporary research topics and application of technologies in SMART tourism analytics. To apply the Big Data analytics and Business Intelligence concepts in the Indian tourism industry and discuss the related case studies covering various subtopics of exclusive destination branding and Market intelligence for knowledge discovery. To evolve Big Data strategy for the specific tourism product design and respective data extraction, transformation, and loading data in the Business Intelligence and data mining tools. To create attractive dashboards for SMART tourism application using storyboarding and Human-Computer Interaction techniques. Visualization techniques for descriptive data analytics and business insights. Intelligent Decision support system for Tourism destination choice.
Practical Natural Language Processing
If you want to build, iterate and scale NLP systems in a business setting and to tailor them for various industry verticals, this is your guide. Consider the task of building a chatbot or text classification system at your organization. In the beginning, there may be little or no data to work with. At this point, a basic solution that uses rule based systems or traditional machine learning will be apt. As you accumulate more data, more sophisticated-and often data intensive-ML techniques can be used including deep learning. At each step of this journey, there are dozens of alternative approaches you can take. This book helps you navigate this maze of options.
Approaches to Measuring Linguistic Differences
The present volume collects contributions addressing different aspects of the measurement of linguistic differences, a topic which probably is as old as language itself but at the same time has acquired renewed interest over the last decade or so, reflecting a rapid development of data-intensive computing in all fields of research, including linguistics.
