books by Jeff Smith, Jr.
Exploring Deep Learning for Language
Near-lifelike chatbots, meaningful resume-to-job matches, and laser-focused product recommendations are just a few examples of what’s possible when you apply deep learning to natural language processing (NLP). Emerging NLP algorithms and machine learning techniques give these amazing systems the ability to determine emotional tone, infer meaning from context, summarize documents, and even generate helpful responses to new questions.
Exploring Deep Learning for Language is a collection of chapters from five Manning books, handpicked by machine learning expert Jeff Smith. This free eBook begins with an overview of natural language processing before moving on to techniques for working with language data. You’ll explore practical techniques like feature generation to help algorithms make sense of your unstructured data and generating synonyms for improving relevant query results. You’ll also get an overview of more advanced topics like using artificial neural networks to model language and embedding natural language in the popular TensorFlow machine learning framework. These carefully-selected chapters deliver a solid foundation for what you can do when you combine deep learning with natural language processing.
Machine Learning Systems
Machine Learning Systems: Designs that scale teaches you to design and implement production-ready ML systems. You'll learn the principles of reactive design as you build pipelines with Spark, create highly scalable services with Akka, and use powerful machine learning libraries like MLib on massive datasets. The examples use the Scala language, but the same ideas and tools work in Java as well.
