A key strength of NLP (natural language processing) is being able to process large amounts of texts and then summarise them to extract meaningful insights.

In this example, a selection of economic bulletins in PDF format from 2018 to 2019 are analysed in order to gauge economic sentiment. The bulletins in question are sourced from the European Central Bank website. tf-idf is used to rank…

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Think back to the last time you texted a chatbot. Whether it was a concierge, a customer support assistant, or an AI…

Summary:  Where do we look to see the most advanced chatbots and the most complete application of AI?  Chatbots designed as ‘artificially intelligent psychological counseling chatbots’, ‘therapeutic assistants’ for short.

Perhaps a better title for this would be “how far have we come?”  About two months ago…

Introduction

Natural language conversation is one of the most challenging artificial intelligence problems, which involves language understanding, reasoning, and the utilization of common sense knowledge. Previous works in this direction mainly focus on either rule-based or learning-based methods. These types of methods often rely on manual effort in designing rules or automatic training of model with a particular learning algorithm and a small amount of data, which…

Text Analytics with Python -- A Practical Real-World Approach to Gaining Actionable Insights from your Data

Text analytics can be a bit overwhelming and frustrating at times with the unstructured and noisy nature of textual data and the vast amount of information available. "Text Analytics with Python" published by Apress\Springer, is a book packed with 385 pages of useful information based on techniques, algorithms,…

Here are three useful resources for learning about Data Science:

• Machine Learning and Deep Learning Tutorial List: This link contains a topic-wise curated list of Machine Learning and Deep Learning tutorials, codes, articles and other resources

• Data Science…