Applied Natural Language Processing with Python Implementing Machine Learning and Deep Learning Algorithms for Natural Language Processing /
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...
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| Main Author: | |
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| Format: | Electronic eBook |
| Language: | English |
| Published: |
Berkeley, CA :
Apress,
2018.
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| Edition: | 1st ed. 2018. |
| Subjects: | |
| ISBN: | 9781484237335 |
| Online Access: |
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|---|---|---|---|
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| 007 | cr nn 008mamaa | ||
| 008 | 180911s2018 xxu| s |||| 0|eng d | ||
| 020 | |a 9781484237335 | ||
| 024 | 7 | |a 10.1007/978-1-4842-3733-5 |2 doi | |
| 035 | |a CVTIDW06900 | ||
| 040 | |a Springer-Nature |b eng |c CVTISR |e AACR2 | ||
| 041 | |a eng | ||
| 100 | 1 | |a Beysolow II, Taweh. |4 aut | |
| 245 | 1 | 0 | |a Applied Natural Language Processing with Python |h [electronic resource] : |b Implementing Machine Learning and Deep Learning Algorithms for Natural Language Processing / |c by Taweh Beysolow II. |
| 250 | |a 1st ed. 2018. | ||
| 260 | 1 | |a Berkeley, CA : |b Apress, |c 2018. | |
| 300 | |a XV, 150 p. 32 illus. |b online resource. | ||
| 500 | |a Professional and Applied Computing | ||
| 505 | 0 | |a Chapter 1: What is Natural Language Processing? -- Chapter 2: Review of Machine Learning -- Chapter 3: Working with Raw Text -- Chapter 4: Word Embeddings and their application -- Chapter 5: Using Machine Learning with Natural Language Processing. | |
| 516 | |a text file PDF | ||
| 520 | |a 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. You will: 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 . | ||
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 0 | |a Python (Computer program language). | |
| 650 | 0 | |a Open source software. | |
| 650 | 0 | |a Computer programming. | |
| 650 | 0 | |a Big data. | |
| 856 | 4 | 0 | |u http://hanproxy.cvtisr.sk/han/cvti-ebook-springer-eisbn-978-1-4842-3733-5 |y Vzdialený prístup pre registrovaných používateľov |
| 910 | |b ZE04180 | ||
| 919 | |a 978-1-4842-3733-5 | ||
| 974 | |a andrea.lebedova |f Elektronické zdroje | ||
| 992 | |a SUD | ||
| 999 | |c 272595 |d 272595 | ||