Deep Learning, NLP, NMT, AI, ML
Introduction In this tutorial, we are going to discuss shallow copies vs deep copies with the help of examples in Python. We will cover the definition of a deep and shallow copy, along with its implementation in the Python language to evaluate the core differences between the two types of copies. In many of the programs that we write, no matter how basic they are, we end up needing to copy a list or an object for one of many […]
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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: […]
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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 […]
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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 […]
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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 […]
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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 […]
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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 […]
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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. […]
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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 […]
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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 […]
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