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Companies are spending billions on machine learning projects, but its money wasted if the models cant be deployed effectively. In this practical guide, Hannes Hapke and Catherine …
Learn how to solve challenging machine learning problems with TensorFlow, Googles revolutionary new software library for deep learning. If you have some background in basic linear …
What value does semantic data modeling offer? As an information architect or data science professional, lets say you have an abundance of the right data and the technology to …
If you want to build an enterprise-quality application that uses natural language text but arent sure where to begin or what tools to use, this practical guide will help get you …
Natural Language Processing (NLP) provides boundless opportunities for solving problems in artificial intelligence, making products such as Amazon Alexa and Google Translate …
Create your own natural language training corpus for machine learning. Whether youre working with English, Chinese, or any other natural language, this hands-on book guides you …
NLP has exploded in popularity over the last few years. But while Google, Facebook, OpenAI, and others continue to release larger language models, many teams still struggle with …
Many books and courses tackle natural language processing (NLP) problems with toy use cases and well-defined datasets. But if you want to build, iterate, and scale NLP systems in a …
Learn how to fuse today's data science tools and techniques with your SAP enterprise resource planning (ERP) system. With this practical guide, SAP veterans Greg Foss and Paul …
Much of the data available today is unstructured and text-heavy, making it challenging for analysts to apply their usual data wrangling and visualization tools. With this practical …