Recognition

PluralSight – Creating Named Entity Recognition Systems with Python

PluralSight – Creating Named Entity Recognition Systems with Python-BOOKWARE-KNiSO
English | Size: 166.79 MB
Category: Tutorial


Release Notes: In this course, Creating Named Entity Recognition Systems with Python, you’ll look at how data professionals and software developers make use of the Python language. First, you’ll explore the unique ability of such systems to perform information retrieval by identifying specific classes of entities in texts Next, you’ll learn how to install prerequisite tools and how to create in a step-by-step manner all the specific components of performant NER systems Finally, you’ll be able to create Named Entity Recognition (NER) systems by leveraging the language s powerful set of open-source NLP libraries. When you re finished with this course, you ll have the skills and knowledge of creating named entity recognition systems with Python

Linkedin Learning – Deep Learning Image Recognition

Linkedin Learning – Deep Learning Image Recognition-ZH
English | Size: 307.54 MB
Category: Tutorial

Thanks to deep learning, image recognition systems have improved and are now used for everything from searching photo libraries to generating text-based descriptions of photographs. In this course, learn how to build a deep neural network that can recognize objects in photographs. Find out how to adjust state-of-the-art deep neural networks to recognize new objects, without the need to retrain the network. Explore cloud-based image recognition APIs that you can use as an alternative to building your own systems. Learn the steps involved to start building and deploying your own image recognition system