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You're reading from  Mastering Transformers

Product typeBook
Published inSep 2021
PublisherPackt
ISBN-139781801077651
Edition1st Edition
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Authors (2):
Savaş Yıldırım
Savaş Yıldırım
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Savaş Yıldırım

Savaş Yıldırım graduated from the Istanbul Technical University Department of Computer Engineering and holds a Ph.D. degree in Natural Language Processing (NLP). Currently, he is an associate professor at the Istanbul Bilgi University, Turkey, and is a visiting researcher at the Ryerson University, Canada. He is a proactive lecturer and researcher with more than 20 years of experience teaching courses on machine learning, deep learning, and NLP. He has significantly contributed to the Turkish NLP community by developing a lot of open source software and resources. He also provides comprehensive consultancy to AI companies on their R&D projects. In his spare time, he writes and directs short films, and enjoys practicing yoga.
Read more about Savaş Yıldırım

Meysam Asgari- Chenaghlu
Meysam Asgari- Chenaghlu
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Meysam Asgari- Chenaghlu

Meysam Asgari-Chenaghlu is an AI manager at Carbon Consulting and is also a Ph.D. candidate at the University of Tabriz. He has been a consultant for Turkey's leading telecommunication and banking companies. He has also worked on various projects, including natural language understanding and semantic search.
Read more about Meysam Asgari- Chenaghlu

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Conventions used

There are a number of text conventions used throughout this book.

Code in text: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "Sequences that are shorter than max_sen_len (maximum sentence length) are padded with a PAD value until they are max_sen_len in length."

A block of code is set as follows:

max_sen_len=max([len(s.split()) for s in sentences])
words = ["PAD"]+ list(set([w for s in sentences for w in s.split()]))
word2idx= {w:i for i,w in enumerate(words)}
max_words=max(word2idx.values())+1
idx2word= {i:w for i,w in enumerate(words)}
train=[list(map(lambda x:word2idx[x], s.split())) for s in sentences]

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

[default]
exten => s,1,Dial(Zap/1|30)
exten => s,2,Voicemail(u100)
exten => s,102,Voicemail(b100)
exten => i,1,Voicemail(s0)

Any command-line input or output is written as follows:

$ conda activate transformers
$ conda install -c conda-forge tensorflow

Bold: Indicates a new term, an important word, or words that you see onscreen. For instance, words in menus or dialog boxes appear in bold. Here is an example: "We must now take care of the computational cost of a particular model for a given environment (Random Access Memory (RAM), CPU, and GPU) in terms of memory usage and speed."

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Mastering Transformers
Published in: Sep 2021Publisher: PacktISBN-13: 9781801077651

Authors (2)

author image
Savaş Yıldırım

Savaş Yıldırım graduated from the Istanbul Technical University Department of Computer Engineering and holds a Ph.D. degree in Natural Language Processing (NLP). Currently, he is an associate professor at the Istanbul Bilgi University, Turkey, and is a visiting researcher at the Ryerson University, Canada. He is a proactive lecturer and researcher with more than 20 years of experience teaching courses on machine learning, deep learning, and NLP. He has significantly contributed to the Turkish NLP community by developing a lot of open source software and resources. He also provides comprehensive consultancy to AI companies on their R&D projects. In his spare time, he writes and directs short films, and enjoys practicing yoga.
Read more about Savaş Yıldırım

author image
Meysam Asgari- Chenaghlu

Meysam Asgari-Chenaghlu is an AI manager at Carbon Consulting and is also a Ph.D. candidate at the University of Tabriz. He has been a consultant for Turkey's leading telecommunication and banking companies. He has also worked on various projects, including natural language understanding and semantic search.
Read more about Meysam Asgari- Chenaghlu