Found insideDive deeper into neural networks and get your models trained, optimized with this quick reference guide Key Features A quick reference to all important deep learning concepts and their implementations Essential tips, tricks, and hacks to ... Found insideThis book bridges theoretical computer science and machine learning by exploring what the two sides can teach each other. Found insideThis book constitutes the refereed proceedings of the 8th International Conference of the CLEF Initiative, CLEF 2017, held in Dublin, Ireland, in September 2017. Learn how to harness the powerful Python ecosystem and tools such as spaCy and Gensim to perform natural language processing, and computational linguistics algorithms. Here's what some of the leading thinkers in the field have to say about it: A sober and easy-to-read review of the risks and opportunities that humanity will face from AI. Jaan Tallinn - co-founder of Skype Understanding AI - its promise ... Entropy Guided Transformation Learning: Algorithms and Applications (ETL) presents a machine learning algorithm for classification tasks. Found insideThe synergistic confluence of linguistics, statistics, big data, and high-performance computing is the underlying force for the recent and dramatic advances in analyzing and understanding natural languages, hence making this series all the ... The text includes exercises and extensive references for further study, and a companion website with source code for all examples and additional debugging resources. This is a valuable resource on the state-of-the- art and future research challenges of multi-modal behavioral analysis in the wild. The International AAAI Conference on Web and Social Media provides an intellectual hub and a stimulating and inspiring environment for researchers in the computational social sciences who are interested in exploring social phenomena with ... Arabic Computational Linguistics documents the recent work of researchers in both academia and industry who have taken up the challenge of solving the real-life problems posed by an understudied language. Found inside – Page iiiThis volume constitutes the refereed proceedings of the Second International Conference on Multimedia and Signal Processing, CMSP 2012, held in Shanghai, China, in December 2012. This book covers the theory, design and applications of computer networks, distributed computing and information systems. Found insideWhat you will learn Implement machine learning techniques to solve investment and trading problems Leverage market, fundamental, and alternative data to research alpha factors Design and fine-tune supervised, unsupervised, and reinforcement ... Found insideThe book covers core areas of sentiment analysis and also includes related topics such as debate analysis, intention mining, and fake-opinion detection. The overflow of information generated during disasters can be as paralyzing to humanitarian response as the lack of information. Found inside – Page iIn the course of telling these stories, Scott touches on a wide variety of subjects: public disorder and riots, desertion, poaching, vernacular knowledge, assembly-line production, globalization, the petty bourgeoisie, school testing, ... Found insideThis book is written primarily for university researchers, graduate students and professional practitioners (assuming an elementary level of linear algebra, probability and statistics, and signal processing) working on medical image ... Found inside – Page iThe second edition of this book will show you how to use the latest state-of-the-art frameworks in NLP, coupled with Machine Learning and Deep Learning to solve real-world case studies leveraging the power of Python. Found insideUsing clear explanations, standard Python libraries and step-by-step tutorial lessons you will discover what natural language processing is, the promise of deep learning in the field, how to clean and prepare text data for modeling, and how ... Found inside – Page 47For Doc2Vec we use the gensim package [21] which provides a most_similar() method that returns the most similar words to a given word in the vocabulary by ... Found inside – Page iWhile highlighting topics including deep learning, query entity recognition, and information retrieval, this book is ideally designed for research and development professionals, IT specialists, industrialists, technology developers, data ... Found inside – Page 246주27 그런 다음 파이썬에서 gensim의 FastText 모듈을 이용해서 해당 파일들로부터 ... ft_model.most_similar('soccer') 일단 모형을 적재한 후에는 gensim의 다른 ... Found inside – Page 386... 0.05287395, 0.07293667, -0.01861257, -0.13574287], The Gensim library provides a rich ... the neural network underlying Doc2Vec has state randomization, ... Reviews the emerging field of geodesic methods and features the following: explanations of the mathematical foundations underlying these methods; discussion on the state of the art algorithms to compute shortest paths; review of several ... Found inside – Page iiThis major work on knowledge representation is based on the writings of Charles S. Peirce, a logician, scientist, and philosopher of the first rank at the beginning of the 20th century. Found insideThis book teaches you to leverage deep learning models in performing various NLP tasks along with showcasing the best practices in dealing with the NLP challenges. Found inside – Page iiThis book: Provides complete coverage of the major concepts and techniques of natural language processing (NLP) and text analytics Includes practical real-world examples of techniques for implementation, such as building a text ... Found insideTopics covered in this volume include discourse theory, mechanical translation, deliberate writing, and revision. Natural Language Generation Systems contains contributions by leading researchers in the field. Pro OGRE 3D Programming offers a detailed guide to the cross-platform Object-Oriented Graphics Rendering Engine (OGRE) 3D engine. Found inside – Page 251 2 from gensim import models from gensim.models import doc2vec 3 4 5 6 documents ... topn=5): 14 15 16 similar_docs = model.docvecs.most_similar(doc_id, ... The tiers are shifting. Found inside – Page ivThis book discusses the application of various statistical methods to texts, rather than numbers, in various fields in behavioral science. This book is based on a Shonan meeting on FLOSS ecosystem sustainability held in June 2017. The meeting brought together a blend of established and young researchers who were actively studying the FLOSS phenomenon. Robert Graham is the editor of Anarchism: A Documentary History of Libertarian Ideas, Volume One: From Anarchy to Anarchism (300CE to 1939). Whether you are trying to build dynamic network models or forecast real-world behavior, this book illustrates how graph algorithms deliver value—from finding vulnerabilities and bottlenecks to detecting communities and improving machine ... Found insidefrom nltk.tokenize import word_tokenize from gensim.models.doc2vec import ... model.docvecs.most_similar([new_vector]) #gives 10 most similar titles ... Found insideWith this practical book, you’ll learn techniques for extracting and transforming features—the numeric representations of raw data—into formats for machine-learning models. This book contains important new contributions from leading researchers at IBM, Google, Microsoft, Thomson Reuters, BBN, CMU, University of Edinburgh, University of Washington, University of North Texas, and others. The book introduces neural networks with TensorFlow, runs through the main applications, covers two working example apps, and then dives into TF and cloudin production, TF mobile, and using TensorFlow with AutoML. This book explains: Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, ... This book includes a set of rigorously reviewed world-class manuscripts addressing and detailing state-of-the-art research projects in the areas of Computer Science, Informatics, and Systems Sciences, and Engineering. Found inside[27] With the following code, you can then load it into gensim: 27 The ... ft_model.most_similar('soccer') 2 3 1 If you're using a gensim version before ... The three volume set provides a systematic overview of theories and technique on social network analysis. In this insightful book, NLP expert Stephan Raaijmakers distills his extensive knowledge of the latest state-of-the-art developments in this rapidly emerging field. Found insideThe aim of the book is to provide latest research findings, innovative research results, methods and development techniques from both theoretical and practical perspectives related to the emerging areas of Web Computing, Intelligent Systems ... Found inside – Page 504The gensim.models.Doc2Vec class processes documents in the TaggedDocument format that contains the tokenized documents alongside a unique tag that permits ... And applications of computer networks, distributed computing and information systems deliberate writing, revision. 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