Python tutorials

Python for NLP: Tokenization, Stemming, and Lemmatization with SpaCy Library

In the previous article, we started our discussion about how to do natural language processing with Python. We saw how to read and write text and PDF files. In this article, we will start working with the spaCy library to perform a few more basic NLP tasks such as tokenization, stemming and lemmatization. Introduction to SpaCy The spaCy library is one of the most popular NLP libraries along with NLTK. The basic difference between the two libraries is the fact […]

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Introduction to Python FTP

Introduction In this tutorial, we will explore how to use FTP with Python to send and receive files from a server over TCP/IP connections. To make things easier and more abstract, we will be using Python’s ftplib library which provides a range of functionalities that make it easier to work with FTP. We’ll see the implementation for uploading and downloading files from the server, as well as some other cool things that “ftplib” allows us to do. What is FTP? […]

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Python for NLP: Vocabulary and Phrase Matching with SpaCy

This is the third article in this series of articles on Python for Natural Language Processing. In the previous article, we saw how Python’s NLTK and spaCy libraries can be used to perform simple NLP tasks such as tokenization, stemming and lemmatization. We also saw how to perform parts of speech tagging, named entity recognition and noun-parsing. However, all of these operations are performed on individual words. In this article, we will move a step further and explore vocabulary and […]

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Basic AI Concepts: A* Search Algorithm

Introduction Artificial intelligence in its core strives to solve problems of enormous combinatorial complexity. Over the years, these problems were boiled down to search problems. A path search problem is a computational problem where you have to find a path from point A to point B. In our case, we’ll be mapping search problems to appropriate graphs, where the nodes represent all the possible states we can end up in and the edges representing all the possible paths that we […]

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Commenting Python Code

Programming reflects your way of thinking in order to describe the single steps that you took to solve a problem using a computer. Commenting your code helps explain your thought process, and helps you and others to understand later on the intention of your code. This allows you to more easily find errors, to fix them, to improve the code later on, and to reuse it in other applications as well. Commenting is important to all kinds of projects, no […]

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Python for NLP: Parts of Speech Tagging and Named Entity Recognition

This is the 4th article in my series of articles on Python for NLP. In my previous article, I explained how the spaCy library can be used to perform tasks like vocabulary and phrase matching. In this article, we will study parts of speech tagging and named entity recognition in detail. We will see how the spaCy library can be used to perform these two tasks. Parts of Speech (POS) Tagging Parts of speech tagging simply refers to assigning parts […]

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Working with PostgreSQL in Python

Introduction PostgreSQL is one of the most advanced and widely used relational database management systems. It’s extremely popular for many reasons, a few of which include it being open source, its extensibility, and its ability to handle many different types of applications and varying loads. With Python, you can easily establish a connection to your PostgreSQL database. There are many Python drivers for PostgreSQL, with “psycopg” being the most popular one. Its current version is psycopg2. In this article, we’ll […]

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Sorting Algorithms in Python

Introduction Sometimes, data we store or retrieve in an application can have little or no order. We may have to rearrange the data to correctly process it or efficiently use it. Over the years, computer scientists have created many sorting algorithms to organize data. In this article we’ll have a look at popular sorting algorithms, understand how they work and code them in Python. We’ll also compare how quickly they sort items in a list. For simplicity, algorithm implementations would […]

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Getting Started with Selenium and Python

Introduction Web Browser Automation is gaining popularity, and many frameworks/tools have arose to offer automation services to developers. Web Browser Automation is often used for testing purposes in development and production environments, though it’s also often used for web scraping data from public sources, analysis, and data processing. Really, what you do with automation is up to you, though, just make sure that what you’re doing is legal, as “bots” created with automation tools can often infringe laws or a […]

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Python for NLP: Sentiment Analysis with Scikit-Learn

This is the fifth article in the series of articles on NLP for Python. In my previous article, I explained how Python’s spaCy library can be used to perform parts of speech tagging and named entity recognition. In this article, I will demonstrate how to do sentiment analysis using Twitter data using the Scikit-Learn library. Sentiment analysis refers to analyzing an opinion or feelings about something using data like text or images, regarding almost anything. Sentiment analysis helps companies in […]

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