Machine Translation with PyTorch
Build, Train, and Deploy Neural Translation Models from Scratch
This book guides you through the complete process of building machine translation systems with PyTorch. You'll start by understanding the core concepts behind neural machine translation, then progress through implementing attention mechanisms, transformer architectures, and training pipelines. Each chapter combines theoretical foundations with hands-on code examples that you can run immediately. You'll learn how to prepare multilingual datasets, design efficient data pipelines, and optimize models for real-world performance. The book covers practical challenges like handling rare words, managing computational resources, and evaluating translation quality beyond standard metrics. By the end, you'll have the knowledge and code patterns needed to build, train, and deploy translation models for production environments. Whether you're working on low-resource language pairs or scaling to millions of translations, this book provides the tools and insights to succeed.
Est. Length
207 pages (10 chapters)
Language
English
Publication date
Jul 3, 2026
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