ISBN: 9789389898781 - python text mining: perform text processing, word embedding, text classification and machine translation (english edition) (23 resultados)

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Paperback. Condición: new. Paperback. Make use of the most advanced machine learning techniques to perform NLP and feature extractionKey FeaturesLearn about pre-trained models, deep learning, and transfer learning for NLP applications.All-in-one knowledge guide for feature engineering, NLP models, and pre-processing techniques.Includes use cases, enterprise deployments, and a range of Python based demonstrations.DescriptionNatural Language Processing (NLP) has proven to be useful in a wide range of applications. Because of this, extracting information from text data sets requires attention to methods, techniques, and approaches.'Python Text Mining' includes a number of application cases, demonstrations, and approaches that will help you deepen your understanding of feature extraction from data sets. You will get an understanding of good information retrieval, a critical step in accomplishing many machine learning tasks. We will learn to classify text into discrete segments solely on the basis of model properties, not on the basis of user-supplied criteria. The book will walk you through many methodologies, such as classification, that will enable you to rapidly construct recommendation engines, subject segmentation, and sentiment analysis applications. Toward the end, we will also look at machine translation and transfer learning.By the end of this book, you'll know exactly how to gather web-based text, process it, and then apply it to the development of NLP applications.What you will learnPractice how to process raw data and transform it into a usable format.Best techniques to convert text to vectors and then transform into word embeddings.Unleash ML and DL techniques to perform sentiment analysis.Build modern recommendation engines using classification techniques.Who this book is forThis book is a good place to start with examples, explanations, and exercises for anyone interested in learning more about advanced text mining and natural language processing techniques. It is suggested but not required that you have some prior programming experience.Table of Contents1. Basic Text Processing Techniques2. Text to Numbers3. Word Embeddings4. Topic Modeling5. Unsupervised Sentiment Classification6. Text Classification Using ML7. Text Classification Using Deep learning8. Recommendation engine9. Transfer LearningRead more Learn advanced NLP techniques like pre-trained models and transfer learning for feature extraction. Covers feature engineering, NLP models, and Python demos. Includes use cases, enterprise deployments, and text mining methodologies for sentiment analysis and recommendation engines. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. …

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Condición: New. KlappentextrnrnNatural Language Processing (NLP) has proven to be useful in a wide range of applications. Because of this, extracting information from text data sets requires attention to methods, techniques, and approaches.n Python Text Mining .

Paperback. Condición: new. Paperback. Make use of the most advanced machine learning techniques to perform NLP and feature extractionKey FeaturesLearn about pre-trained models, deep learning, and transfer learning for NLP applications.All-in-one knowledge guide for feature engineering, NLP models, and pre-processing techniques.Includes use cases, enterprise deployments, and a range of Python based demonstrations.DescriptionNatural Language Processing (NLP) has proven to be useful in a wide range of applications. Because of this, extracting information from text data sets requires attention to methods, techniques, and approaches.'Python Text Mining' includes a number of application cases, demonstrations, and approaches that will help you deepen your understanding of feature extraction from data sets. You will get an understanding of good information retrieval, a critical step in accomplishing many machine learning tasks. We will learn to classify text into discrete segments solely on the basis of model properties, not on the basis of user-supplied criteria. The book will walk you through many methodologies, such as classification, that will enable you to rapidly construct recommendation engines, subject segmentation, and sentiment analysis applications. Toward the end, we will also look at machine translation and transfer learning.By the end of this book, you'll know exactly how to gather web-based text, process it, and then apply it to the development of NLP applications.What you will learnPractice how to process raw data and transform it into a usable format.Best techniques to convert text to vectors and then transform into word embeddings.Unleash ML and DL techniques to perform sentiment analysis.Build modern recommendation engines using classification techniques.Who this book is forThis book is a good place to start with examples, explanations, and exercises for anyone interested in learning more about advanced text mining and natural language processing techniques. It is suggested but not required that you have some prior programming experience.Table of Contents1. Basic Text Processing Techniques2. Text to Numbers3. Word Embeddings4. Topic Modeling5. Unsupervised Sentiment Classification6. Text Classification Using ML7. Text Classification Using Deep learning8. Recommendation engine9. Transfer LearningRead more Learn advanced NLP techniques like pre-trained models and transfer learning for feature extraction. Covers feature engineering, NLP models, and Python demos. Includes use cases, enterprise deployments, and text mining methodologies for sentiment analysis and recommendation engines. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. …

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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Natural Language Processing (NLP) has proven to be useful in a wide range of applications. Because of this, extracting information from text data sets requires attention to methods, techniques, and approaches.'Python Text Mining' includes a number of application cases, demonstrations, and approaches that will help you deepen your understanding of feature extraction from data sets. You will get an understanding of good information retrieval, a critical step in accomplishing many machine learning tasks. We will learn to classify text into discrete segments solely on the basis of model properties, not on the basis of user-supplied criteria. The book will walk you through many methodologies, such as classification, that will enable you to rapidly construct recommendation engines, subject segmentation, and sentiment analysis applications. Toward the end, we will also look at machine translation and transfer learning.By the end of this book, you'll know exactly how to gather web-based text, process it, and then apply it to the development of NLP applications.1. Basic Text Processing Techniques2. Text to Numbers3. Word Embeddings4. Topic Modeling5. Unsupervised Sentiment Classification6. Text Classification Using ML7. Text Classification Using Deep learning8. Recommendation engine9. Transfer Learning.…

Taschenbuch. Condición: Neu. Python Text Mining | Perform Text Processing, Word Embedding, Text Classification and Machine Translation | Alexandra George | Taschenbuch | Kartoniert / Broschiert | Englisch | 2022 | BPB Publications | EAN 9789389898781 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. …