Supply shortages, increasing prices, and a tight supply chain ecosystem have forced the supply chain leaders globally to innovate. The tool driving this innovation is Artificial Intelligence. Forward-thinking organizations are using AI to innovate in all areas of supply chain management(SCM).
Structured Approach to Extract Information from Unstructured Documents 📜 Much has been explored & conquered in the field of structured datasets (tabular data, invoices, etc) we have predefined steps to follow to get decent results but to extract information from unstructured documents (insurance docs, contracts, medical reports, etc) there is no such guide
Text similarity is to calculate how two words/phrases/documents are close to each other. That closeness may be lexical or in meaning.
Solve complex NLP tasks using these 5 lesser known Python libraries: 1. Textstat is an easy to use library to calculate text data statistics, such as reading time and word count. It also assign a readability score to your text to help determine its complexity and grade level.
We’ll look at the various categories of AI being employed and provide a framework for how companies should begin to build up their cognitive capabilities in the next several years to achieve their business objectives.
Until recently, the conventional wisdom was that while AI was better than humans at data-driven decision-making tasks, it was still inferior to humans for cognitive and creative ones. But in the past two years, language-based AI has advanced by leaps and bounds, changing common notions of what this technology can do.
Natural Language Generation is the “process of producing meaningful phrases and sentences in the form of natural language.” In its essence, it automatically generates narratives that describe, summarize or explain input structured data in a human-like manner at the speed of thousands of pages per second.
Visualisations are often the way to go! Psychologically, our brain feels less strained inspecting this visualisation than it would if it had to inspect this data in a list structure.
Deep learning concepts Part #5,
Feature selection is the process of reducing the number of input variables when developing a predictive model.
It is desirable to reduce the number of input variables to both reduce the computational cost of modeling and, in some cases, to improve the performance of the model.