000			01707nam a22002897i 4500
005			20250821114254.0
008			250723s2021 ii ao||fr|||| 00| 0 eng d
020			_a9789389898118
040			_aEG-GaU‬‬ _cEG-GaU‬‬ _dEG-GaU‬‬ _erda
082	0	4	_223 _a006.31 _bP.S.G
100	1		_aPatel, Sunil, _eauthor. _963120
245	1	0	_aGetting Started with Deep Learning for Natural Language Processing : _blearn how to build NLP applications with Deep Learning / _cSunil Patel.
250			_aFirst edition.
264		1	_aNew Delhi : _bBPB Publications, _c2021.
300			_a 382 pages ; _c24 cm.
336			_2rdacontent _atext _btxt
337			_2rdamedia _aunmediated _bn
338			_2rdacarrier _avolume _bnc
504			_aIncludes index.
505			_a1. Understanding the basics of learning process -- 2. Text processing techniques -- 3. Representing language mathematically -- 4. Using RNN for NLP -- 5. Applying CNN in NLP tasks -- 6. Accelerating NLP with advanced embeddings -- 7. Applying deep learning to NLP tasks -- 8. Application of complex architectures in NLP -- 9. Understanding generative networks -- 10. Techniques of speech processing -- 11. The road ahead.
520			_aCovers foundational and advanced deep learning techniques applied to Natural Language Processing (NLP) using Python and PyTorch. Includes preprocessing, CNNs, RNNs, Transformers, GANs, speech processing, and practical applications in topic modeling, text generation, and more.
650		0	_aDeep learning. _963119
650		0	_aNatural language processing (Computer science). _962030
650		0	_aPython (Computer program language).
942			_2ddc _cBK
999			_c11091 _d11091