Natural language processing of Samuel Pepys’ Diary

Samuel Pepys was a 17th century Englishman who kept a daily diary for 10 years which gives us a unique insight of life in Stuart England and includes eye-witness accounts of events such as the Great Fire of London and the Great Plague of London. I have started a project to analyse the text from the diary using common Python NLP libraries in order try and use data from the texts to find insights into Pepys’ thoughts and life. The […]

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A Product lead’s Guide to NLP solutions

A not-too-technical guide to find the ideal text analytics solution for your application If you are leading a digital product development that transforms unstructured text into value for your internal / external users, yet have difficulties navigating through the Natural Language Processing (NLP) solutions or making the build-or-buy decision, this article helps you identify key decision criteria to make informed choice.

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Adversarial Attacks on Question Answering

The recent explosion of Question Answering datasets and models is pushing the boundaries of QA systems and making them widely used by the general public in virtual assistants or chatbots (Rogers et al., 2021). However, it is well-known that is possible to “trick” machine learning systems. For instance, Goodfellow et al. (2014) shows that a clear picture of a panda can be modified with some invisible noise for humans that makes the ML model classify it as a    

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Getters and Setters: Manage Attributes in Python

If you come from a language like Java or C++, then you’re probably used to writing getter and setter methods for every attribute in your classes. These methods allow you to access and mutate private attributes while maintaining encapsulation. In Python, you’ll typically expose attributes as part of your public API and use properties when you need attributes with functional behavior. Even though properties are the Pythonic way to go, they can have some practical drawbacks. Because of this, you’ll […]

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