Gain the knowledge of various deep neural network architectures and their application areas to conquer your NLP issues.
Applying deep learning approaches to various NLP tasks can take your computational algorithms to a completely new level in terms of speed and accuracy. Deep Learning for Natural Language Processing starts off by highlighting the basic building blocks of the natural language processing domain. The book goes on to introduce the problems that you can solve using state-of-the-art neural network models. After this, delving into the various neural network architectures and their specific areas of application will help you to understand how to select the best model to suit your needs. As you advance through this deep learning book, you'll study convolutional, recurrent, and recursive neural networks, in addition to covering long short-term memory networks (LSTM). Understanding these networks will help you to implement their models using Keras. In the later chapters, you will be able to develop a trigger word detection application using NLP techniques such as attention model and beam search.
By the end of this book, you will not only have sound knowledge of natural language processing but also be able to select the best text pre-processing and neural network models to solve a number of NLP issues.
If you're an aspiring data scientist looking for an introduction to deep learning in the NLP domain, this is just the book for you. Strong working knowledge of Python, linear algebra, and machine learning is a must.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Karthiek Reddy Bokka is a Speech and Audio Machine Learning Engineer graduated from University of Southern California and currently working for Biamp Systems in Portland. His interests include Deep Learning, Digital Signal and Audio Processing, Natural Language Processing, Computer Vision. He has experience in designing, building, deploying applications with Artificial Intelligence to solve real-world problems with varied forms of practical data, including Image, Speech, Music, unstructured raw data etc.
Shubhangi Hora is a Python developer, Artificial Intelligence enthusiast, and writer. With a background in Computer Science and Psychology, she is particularly interested in mental health related AI. Shubhangi is based in Pune, India and is passionate about furthering natural language processing through machine learning and deep learning. Aside from this, she enjoys the performing arts and is a trained musician.
Tanuj Jain is a data scientist working at a Germany-based company. He has a master's degree in electrical engineering with a focus on statistical pattern recognition. He has been developing deep learning models and putting them in production for commercial use at his current job. Natural language processing is a special interest area for him and he has applied his know-how to classification and sentiment rating tasks.
Monicah Wambugu is the lead Data Scientist at Loanbee, a financial technology company that offers micro-loans by leveraging on data, machine learning and analytics to perform alternative credit scoring. She is a graduate student at the School of Information at UC Berkeley Masters in Information Management and Systems. Monicah is particularly interested in how data science and machine learning can be used to design products and applications that respond to the behavioral and socio-economic needs of target audiences.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
EUR 17,02 expédition depuis Etats-Unis vers France
Destinations, frais et délaisEUR 4,57 expédition depuis Royaume-Uni vers France
Destinations, frais et délaisVendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Etat : New. In. N° de réf. du vendeur ria9781838550295_new
Quantité disponible : Plus de 20 disponibles
Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
PAP. Etat : New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. N° de réf. du vendeur L0-9781838550295
Quantité disponible : Plus de 20 disponibles
Vendeur : California Books, Miami, FL, Etats-Unis
Etat : New. N° de réf. du vendeur I-9781838550295
Quantité disponible : Plus de 20 disponibles
Vendeur : Chiron Media, Wallingford, Royaume-Uni
PF. Etat : New. N° de réf. du vendeur 6666-IUK-9781838550295
Quantité disponible : 10 disponible(s)
Vendeur : BargainBookStores, Grand Rapids, MI, Etats-Unis
Paperback or Softback. Etat : New. Deep Learning for Natural Language Processing 1.41. Book. N° de réf. du vendeur BBS-9781838550295
Quantité disponible : 5 disponible(s)
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 35873869
Quantité disponible : 1 disponible(s)
Vendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
Paperback / softback. Etat : New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 641. N° de réf. du vendeur C9781838550295
Quantité disponible : Plus de 20 disponibles
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : New. N° de réf. du vendeur 35873869-n
Quantité disponible : 1 disponible(s)
Vendeur : Majestic Books, Hounslow, Royaume-Uni
Etat : New. Print on Demand pp. 372. N° de réf. du vendeur 384434256
Quantité disponible : 4 disponible(s)
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Etat : New. N° de réf. du vendeur 35873869-n
Quantité disponible : Plus de 20 disponibles