Python tutorials

September 25, 2020 Python

Python for NLP: Introduction to the Pattern Library

This is the eighth article in my series of articles on Python for NLP. In my previous article, I explained how Python’s TextBlob library can be used to perform a variety of NLP tasks ranging from tokenization to POS tagging, and text classification to sentiment analysis. In this article, we will explore Python’s Pattern library, which is another extremely useful Natural Language Processing library. The Pattern library is a multipurpose library capable of handling the following tasks: Natural Language Processing: […]

September 25, 2020 Python

Analysis of Black Friday Shopping Trends via Machine Learning

Introduction Wikipedia defines Black Friday as an informal name for the Friday following Thanksgiving Day in the United States, which is celebrated on the fourth Thursday of November. [Black Friday is] regarded as the beginning of America’s Christmas shopping season […]. In this article, we will try to explore different trends from the Black Friday shopping dataset. We will extract useful information that will answer questions such as: what gender shops more on Black Friday? Do the occupations of the […]

September 25, 2020 Python

Constraint Programming with python-constraint

Introduction The first thing we have to understand while dealing with constraint programming is that the way of thinking is very different from our usual way of thinking when we sit down to write code. Constraint programming is an example of the declarative programming paradigm, as opposed to the usual imperative paradigm that we use most of the time. What is a programming paradigm? A paradigm means “an example” or “a pattern” of something. A programming paradigm is often described […]

September 25, 2020 Python

The Python Math Library

Introduction The Python Math Library provides us access to some common math functions and constants in Python, which we can use throughout our code for more complex mathematical computations. The library is a built-in Python module, therefore you don’t have to do any installation to use it. In this article, we will be showing example usage of the Python Math Library’s most commonly used functions and constants. Special Constants The Python Math Library contains two important constants. Pie The first […]

September 25, 2020 Python

Python for NLP: Getting Started with the StanfordCoreNLP Library

This is the ninth article in my series of articles on Python for NLP. In the previous article, we saw how Python’s Pattern library can be used to perform a variety of NLP tasks ranging from tokenization to POS tagging, and text classification to sentiment analysis. Before that we explored the TextBlob library for performing similar natural language processing tasks. In this article, we will explore StanfordCoreNLP library which is another extremely handy library for natural language processing. We will […]

September 25, 2020 Python

Overview of Classification Methods in Python with Scikit-Learn

Introduction Are you a Python programmer looking to get into machine learning? An excellent place to start your journey is by getting acquainted with Scikit-Learn. Doing some classification with Scikit-Learn is a straightforward and simple way to start applying what you’ve learned, to make machine learning concepts concrete by implementing them with a user-friendly, well-documented, and robust library. What is Scikit-Learn? Scikit-Learn is a library for Python that was first developed by David Cournapeau in 2007. It contains a range […]

September 25, 2020 Python

Test Driven Development with pytest

Introduction Good software is tested software. Testing our code can help us catch bugs or unwanted behavior. Test Driven Development (TDD) is a software development practice that requires us to incrementally write tests for features we want to add. It leverages automated testing suites, like pytest – a testing framework for Python programs. Automated Testing Developers usually write code, compile it if necessary, and then run the code to see if it works. This is an example of manual testing. […]

September 25, 2020 Python

Python for NLP: Working with the Gensim Library (Part 1)

This is the 10th article in my series of articles on Python for NLP. In my previous article, I explained how the StanfordCoreNLP library can be used to perform different NLP tasks. In this article, we will explore the Gensim library, which is another extremely useful NLP library for Python. Gensim was primarily developed for topic modeling. However, it now supports a variety of other NLP tasks such as converting words to vectors (word2vec), document to vectors (doc2vec), finding text […]

September 25, 2020 Python

Introduction to Reinforcement Learning with Python

Introduction Reinforcement Learning is definitely one of the most active and stimulating areas of research in AI. The interest in this field grew exponentially over the last couple of years, following great (and greatly publicized) advances, such as DeepMind’s AlphaGo beating the word champion of GO, and OpenAI AI models beating professional DOTA players. Thanks to all of these advances, Reinforcement Learning is now being applied in a variety of different fields, from healthcare to finance, from chemistry to resource […]

September 25, 2020 Python

Working with PDFs in Python: Adding Images and Watermarks

This article is the second in a series on working with PDFs in Python: Introduction Today, a world without the Portable Document Format (PDF) seems to be unthinkable. It has become one of the most commonly used data formats ever. Up to PDF version 1.4, displaying a PDF document in an according PDF viewer works fine. Unfortunately, the features from the newer PDF revisions, such as forms, are tricky to implement, and still require further work to be fully functional […]

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