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035   $a(OCoLC)1090069406
035   $a(OCoLC)on1090069406
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100   $a20190129d2019      u|         0
101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
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200 10$aNatural Language Processing Recipes $eUnlocking Text Data with Machine Learning and Deep Learning using Python /$fby Akshay Kulkarni, Adarsha Shivananda
205   $a1st ed. 2019.
210  1$aBerkeley, CA :$cApress :$cImprint: Apress,$d2019.
215   $a1 online resource (XXV, 234 p. 54 illus.) 
311   $a1-4842-4266-1 
327   $aChapter 1: Extracting the data -- Chapter 2: Exploring and processing text data -- Chapter 3: Converting text to features -- Chapter 4: Advanced natural language processing -- Chapter 5: Implementing Industry Applications -- Chapter 6: Deep learning for NLP.
330   $aImplement natural language processing applications with Python using a problem-solution approach. This book has numerous coding exercises that will help you to quickly deploy natural language processing techniques, such as text classification, parts of speech identification, topic modeling, text summarization, and sentiment analysis. Natural Language Processing Recipes starts by offering solutions for cleaning and preprocessing text data and ways to analyze it with advanced algorithms. You?ll see practical applications of the semantic as well as syntactic analysis of text, as well as complex natural language processing approaches that involve text normalization, advanced preprocessing, POS tagging, parsing, text summarization, and sentiment analysis. You will also learn various applications of machine learning and deep learning in natural language processing. By using the recipes in this book, you will have a toolbox of solutions to apply to your own projects in the real world, making your development time quicker and more efficient. You will: Apply NLP techniques using Python libraries such as NLTK, TextBlob, spaCy, Stanford CoreNLP, and many more Implement the concepts of information retrieval, text summarization, sentiment analysis, and other advanced natural language processing techniques. Identify machine learning and deep learning techniques for natural language processing and natural language generation problems.
606   $aArtificial intelligence
606   $aPython (Computer program language)
606   $aOpen source software
606   $aComputer programming
606   $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000
606   $aPython$3https://scigraph.springernature.com/ontologies/product-market-codes/I29080
606   $aOpen Source$3https://scigraph.springernature.com/ontologies/product-market-codes/I29090
615  0$aArtificial intelligence.
615  0$aPython (Computer program language).
615  0$aOpen source software.
615  0$aComputer programming.
615 14$aArtificial Intelligence.
615 24$aPython.
615 24$aOpen Source.
676   $a006.3
700   $aKulkarni$b Akshay$4aut$4http://id.loc.gov/vocabulary/relators/aut$01376507
702   $aShivananda$b Adarsha$4aut$4http://id.loc.gov/vocabulary/relators/aut
801  0$bUMI
801  1$bUMI
906   $aBOOK
912   $a9910735383503321
996   $aNatural language processing recipes$93412400
997   $aUNINA