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Learn the skills necessary to design, build, and deploy applications powered by machine learning (ML). Through the course of this hands-on book, you’ll build an example ML-driven …
Most data scientists and engineers today rely on quality labeled data to train machine learning models. But building a training set manually is time-consuming and expensive, …
Most of the high-profile cases of real or perceived unethical activity in data science aren’t matters of bad intent. Rather, they occur because the ethics simply aren’t thought …
What value does semantic data modeling offer? As an information architect or data science professional, let’s say you have an abundance of the right data and the technology to …
Learn how to build and operationalize machine learning forecast models for your everyday projects. With this practical book, experienced and novice data scientists, business …
A deluge of digital content is generated daily by web-based platforms and sensors that capture digital traces of communication and connection, and complex states of society, the …
If you want to build an enterprise-quality application that uses natural language text but aren't sure where to begin or what tools to use, this practical guide will help get you …
Graph data closes the gap between the way humans and computers view the world. While computers rely on static rows and columns of data, people navigate and reason about life …
This concise, easy-to-use reference puts one of the most popular frameworks for deep learning research and development at your fingertips. Author Joe Papa provides instant access …
The widespread adoption of AI and machine learning is revolutionizing many industries today. Once these technologies are combined with the programmatic availability of historical …