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Titlebook: Applied Natural Language Processing with Python; Implementing Machine Taweh Beysolow II Book 2018 Taweh Beysolow II 2018 Natural Language P

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發(fā)表于 2025-3-21 18:18:54 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Applied Natural Language Processing with Python
期刊簡稱Implementing Machine
影響因子2023Taweh Beysolow II
視頻videohttp://file.papertrans.cn/160/159990/159990.mp4
發(fā)行地址Covers NLP packages such as NLTK, gensim,and SpaCy.Approaches topics such as "topic modeling" and "text summarization" in a beginner-friendly manner.Explains how to ingest text data via web crawlers f
圖書封面Titlebook: Applied Natural Language Processing with Python; Implementing Machine Taweh Beysolow II Book 2018 Taweh Beysolow II 2018 Natural Language P
影響因子Learn to harness the power of AI for natural language processing, performing tasks such as spell check, text summarization, document classification, and natural language generation. Along the way, you will learn the skills to implement these methods in larger infrastructures to replace existing code or create new algorithms.?.Applied Natural Language Processing with Python?.starts with reviewing the necessary machine learning concepts before moving onto discussing various NLP problems. After reading this book, you will have the skills to apply these concepts in your own professional environment..What You Will Learn??.Utilize various machine learning and natural language processing libraries such as TensorFlow, Keras, NLTK, and Gensim.Manipulate and preprocess raw text data in formats such as .txt and .pdf.Strengthen your skills in data science by learning both the theory and the application of various algorithms??.Who This Book Is For?.You should be at least a beginner in ML to get the most out of this text, but you needn’t feel that you need be an expert to understand the content..
Pindex Book 2018
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發(fā)表于 2025-3-21 23:06:22 | 只看該作者
Review of Deep Learning,ive review of ML/DL, it is critical to discuss a few neural network models because we will be applying them later. This chapter also briefly familiarizes you with TensorFlow, which is one of the frameworks utilized during the course of the book. All examples in this chapter use toy numerical data se
板凳
發(fā)表于 2025-3-22 00:31:02 | 只看該作者
https://doi.org/10.1007/978-1-4842-3733-5Natural Language Processing; Machine Learning; Deep Learning; Python; TensorFlow; Keras; Caffee; Neural Net
地板
發(fā)表于 2025-3-22 05:20:52 | 只看該作者
978-1-4842-3732-8Taweh Beysolow II 2018
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發(fā)表于 2025-3-22 12:05:13 | 只看該作者
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發(fā)表于 2025-3-22 15:35:53 | 只看該作者
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發(fā)表于 2025-3-22 17:43:20 | 只看該作者
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發(fā)表于 2025-3-22 23:41:51 | 只看該作者
Margit Meyer,Egbert Kern,Hans-J?rg DiehlNow that you have had an introduction to working with text data, let’s dive into one of the more advanced feature extraction algorithms. To accomplish some of the more difficult problems, it is reasonable for me to introduce you to other techniques to approach NLP problems. We will move through Word2Vec, Doc2Vec, and GloVe.
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發(fā)表于 2025-3-23 02:26:08 | 只看該作者
Margit Meyer,Egbert Kern,Hans-J?rg DiehlIn Chapter 4, I introduced you to some of the more advanced deep learning and NLP techniques, and I discussed how to implement these models in some basic problems, such as mapping word vectors. Before we conclude this book, I will discuss a handful of other NLP tasks that are more domain-specific, but nonetheless useful to go through.
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發(fā)表于 2025-3-23 05:50:54 | 只看該作者
Topic Modeling and Word Embeddings,Now that you have had an introduction to working with text data, let’s dive into one of the more advanced feature extraction algorithms. To accomplish some of the more difficult problems, it is reasonable for me to introduce you to other techniques to approach NLP problems. We will move through Word2Vec, Doc2Vec, and GloVe.
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