Category: Python

Python tutorials

Natural Language Processing, Python

BERT Explained

The continuous innovation around contextual understanding of sentences has expanded significant bounds in NLP. The general idea of Transformer architecture is based on self-attention proposed in Attention is All You Need paper 2017.Self-attention is learning to weigh the relationship between each item/word to    

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Natural Language Processing, Python

Abstractive text summarization with transformer-based models

Text summarization is a text generation task, which generates a concise and precise summary of input texts. There are two kinds of summarization tasks in Natural Language Processing, one is the extractive approach, which is to identify the most important sentences or phrases in the original text and combine them to make a summary. The more advanced approach is the abstractive approach, which generates new phrases and sentences to represent the information from the input text.

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Python

Python Basics: Scopes

On your Python journey, you’ve probably learned about functions and loops. To fully understand functions and loops in Python, you need to be familiar with the issue of scope. By the end of this video course, you’ll know: What a scope is and why it’s important How Python applies the LEGB rule for scope resolution Scope can be one of the more difficult programming concepts to understand, so in this video course, you’ll get a gentle introduction to it. This […]

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Python

Python’s doctest: Document and Test Your Code at Once

Are you interested in writing usage examples for your code that work as documentation and test cases simultaneously? If your answer is yes, then Python’s doctest module is for you. This module provides a testing framework that doesn’t have too steep a learning curve. It’ll allow you to use code examples for two purposes: documenting and testing your code. Apart from allowing you to use your code’s documentation for testing the code itself, doctest will help you keep your code […]

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Python

My “Aha Moment” About Python

I’ve been programming for about 20 years now, and my “aha moment” with python came to me last night. It was a pretty simple one — I started with Python 2 because that’s what we’re using at work (and it was free). But after some trial and error, I figured out how to get started quickly with Python 3.

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