★Understand everything from the basics of natural language processing to trending technologies from scratch! We will also introduce many techniques for preprocessing and improving accuracy that are useful in practice.
●Understand by purpose! Essential technologies for implementing various processing methods and applications ●Learn hands-on! How to create a document classification model ⇒ Based on example problems, we will explain step by step the preparation of data, preprocessing, fine-tuning settings, etc., along with abundant source code. ●Directly linked to improving processing accuracy! Practical "preprocessing" methods and implementations ⇒ How to handle proper nouns? What measures to take for notation variations? Introduction of useful tools and libraries, etc. ●Research and development trends and application examples by application ⇒ Proposing approaches to challenges encountered in practice, such as dealing with data shortages and unknown words not present in training data, recognition of domain-specific proper expressions, and ways to utilize datasets.
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basic information
Publication Date: March 18, 2020 Price: 40,000 yen + tax Format: B5 size, 180 pages ISBN: 978-4-86502-182-0 [List of Contributors (Honorifics omitted)] ● Jun Suzuki (Tohoku University) ● Seiji Tsuchiya (Doshisha University) ● Kazuki Motohashi (Konduit Inc.) ● Kanji Takahashi (Sansan Inc.) ● Akihiro Tamura (Ehime University) ● Ikuya Yamada (Studio Ousia Inc.) ● Kenji Araki (Hokkaido University) ● Shinsuke Mori (Kyoto University) ● Shinichi Watanabe (Utsunomiya University) ● Shin Hara (Utsunomiya University) ● Tomoya Mizumoto (Future Inc.) ● Takeshi Shimizu (CINC Inc.)
Price information
Regular price: 40,000 yen + tax [Early bird discount available] 35,000 yen + tax *Until March 26, 2020
Price range
P2
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※Same-day shipping for applications received by 3 PM.
Applications/Examples of results
Chapter 1: Introduction - From the Basics of Natural Language Processing to Topics of Discussion Chapter 2: Selection of Methods Based on Data and Objectives 1. Meaning Understanding 2. Extraction of Words and Topics 3. Document Classification 4. Document Summarization 5. Information Retrieval 6. Casual Conversation Dialogue Chapter 3: Hands-On Learning for Creating Document Classification Models and Using Tools Chapter 4: Types of Preprocessing and Implementation Methods - A Gateway to Improving Processing Accuracy Chapter 5: Application-Specific Examples and Proposals for Utilization Section 1: Neural Machine Translation Using Deep Learning Techniques Section 2: Development Trends and Application Cases of Question-Answering Technologies Section 3: Casual Conversation Technologies Using Natural Language Processing Techniques Section 4: Named Entity Recognition Based on Machine Learning Section 5: Development of a Review Classification Support System Using Sentiment Analysis Section 6: Grammar Error Correction for Second Language Learners - Correction Techniques, Learning Data, and Performance Evaluation Methods Section 7: Development of a Sentiment Classifier Targeting Japanese Sentences
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