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Mastering spaCy: An end-to-end practical guide to implementing NLP applications using the Python ecosystem
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What makes this book stand out is that it’s the first to cover spaCy in depth.
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Detalji o proizvodu
| Publisher | Packt Publishing |
| Publication date | July 9, 2021 |
| Language | English |
| Print length | 356 pages |
| ISBN-10 | 1800563353 |
| ISBN-13 | 978-1800563353 |
| Item Weight | 1.35 pounds (610 grams) |
| Dimensions | 7.5 x 0.81 x 9.25 inches (19.1 x 2.1 x 23.5 cm) |
Who Should Buy?
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NLP Beginners
Ideal for those new to Natural Language Processing, providing step-by-step guidance on using spaCy effectively.
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Python Developers
Perfect for Python developers looking to enhance their skills in NLP and integrate these applications into existing projects.
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Data Scientists
Beneficial for data scientists wanting to incorporate NLP into their analysis and utilize text data for insights.
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Advanced Researchers
Not suitable for seasoned NLP researchers seeking in-depth theoretical concepts beyond practical application-focused content.
OPIS PROIZVODA
Mastering spaCy: An end-to-end practical guide to implementing NLP applications using the Python ecosystem
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Intelligence & Semantics Editorial Review
Mastering spaCy is a comprehensive guide that covers the end-to-end process of implementing natural language processing applications using Python. The book provides solid and structured content, making it easy for beginners to understand the basics of spaCy. The author shares a wealth of knowledge in the book, but readers may face challenges due to poor editing. Many lines of code are incorrect or missing, and readers will have to spend additional time researching to obtain the correct codes. Despite these challenges, the book provides a good learning experience for readers who are patient enough to troubleshoot the errors.
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Pros
- Solid and well-structured content
- Comprehensive guide to implementing natural language processing applications
Cons
- Poor editing, with frequent typos, errors in code, and lines that are missing
Product Price History
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Karakteristike i prednosti
- Comprehensive resource for learning spaCy
- Real-world knowledge and examples included
- Explains linguistic concepts behind spaCy components
- Author has firsthand experience as a user and contributor to spaCy
- Includes topics relevant to Conversational AI and NLP development toolbox
- Focuses on fun techniques for information extraction and chatbot design
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