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Item #:
241393330
Hands-on Computational Linguistics With Machine Learning
Item #:
241393330
KWD 13
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This practical guide equips you to bridge the gap between human language and machine intelligence.
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What Stands Out
Practical Application
Engages learners with real-world examples, enabling hands-on experience in computational linguistics and machine learning for effective skill development.
Cutting-Edge Tools
Utilizes the latest technologies and algorithms, ensuring students are well-versed in the current trends and practices in the rapidly evolving field.
Enhanced Learning
Integrates theoretical concepts with practical exercises, reinforcing understanding and preparing learners for advanced challenges in computational linguistics.
Product Details
| Publisher | Independently published |
| Publication date | September 14, 2025 |
| Language | English |
| Print length | 156 pages |
| ISBN-13 | 979-8265356079 |
| Item Weight | 10.4 ounces (294.84 grams) |
| Dimensions | 6.24 x 0.55 x 9.24 inches (15.8 x 1.4 x 23.5 cm) |
Who Should Buy?
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Students and Learners
Perfect for students looking to understand computational linguistics with practical machine learning applications through hands-on projects.
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Data Scientists
Ideal for data scientists wanting to expand their skills in natural language processing and its integration with machine learning.
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Industry Professionals
Beneficial for professionals in tech companies who aim to apply machine learning techniques in linguistics-based projects.
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Absolute Beginners
Not suitable for those with no prior knowledge of programming or machine learning concepts, as foundational knowledge is essential.
Product Description
Hands-on Computational Linguistics With Machine Learning
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KWD 13
Order now and get it around Wednesday, November 04
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Features & Benefits
- Explore the intersection of language, data, and AI.
- Learn core concepts of computational linguistics and machine learning.
- Complete hands-on projects like chatbots and fake news detectors.
- Dive into advanced topics such as transformers and multimodal NLP.
- Address ethical challenges in AI applications.
- Ideal for students, researchers, and curious learners.
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