Deep Learning, NLP, NMT, AI, ML
Python tutorials
Introduction In this article we’ll be taking a look at Global and Non-Local Variables in Python and how you to use them to avoid issues when writing code. We’ll be starting off with a brief primer on variable scopes before we launch into the how and why of using global and non-local variables in your own functions. Scopes in Python Before we can get started, we first have to touch on scopes. For those of you who are less familiar, […]
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Introduction News media has become a channel to pass on the information of what’s happening in the world to the people living. Often people perceive whatever conveyed in the news to be true. There were circumstances where even the news channels acknowledged that their news is not true as they wrote. But some news has a significant impact not only on the people or
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Introduction A heatmap is a data visualization technique that uses color to show how a value of interest changes depending on the values of two other variables. For example, you could use a heatmap to understand how air pollution varies according to the time of day across a set of cities. Another, perhaps more rare case of using heatmaps is to observe human behavior – you can create visualizations of how people use social media, how their answers on surveys […]
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Introduction Hypertext Markup Language (HTML) is the standard markup language for building web pages. We can render tabular data using HTML’s element. The Pandas data analysis library provides functions like read_html() and to_html() so we can import and export data to DataFrames. In this article, we will learn how to read tabular data from an HTML file and load it into a Pandas DataFrame. We’ll also learn how to write data from a Pandas DataFrame and to an HTML file. […]
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Introduction Matplotlib is one of the most widely used data visualization libraries in Python. From simple to complex visualizations, it’s the go-to library for most. In this tutorial, we’ll take a look at how to plot a line plot in Matplotlib – one of the most basic types of plots. Line Plots display numerical values one one axis, and categorical values on the other. They can typically be used in much the same way Bar Plots can be used, though, […]
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Introduction There are many data visualization libraries in Python, yet Matplotlib is the most popular library out of all of them. Matplotlib’s popularity is due to its reliability and utility – it’s able to create both simple and complex plots with little code. You can also customize the plots in a variety of ways. In this tutorial, we’ll cover how to plot Violin Plots in Matplotlib. Violin plots are used to visualize data distributions, displaying the range, median, and distribution […]
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Introduction Python is supported by many libraries which simplify data transfer over HTTP. The requests library is one of the most popular Python packages as it’s heavily used in web scraping. It’s also popular for interacting with servers! The library makes it easy to upload data in a popular format like JSON, but also makes it easy to upload files as well. In this tutorial, we will take a look at how to upload files using Python’s requests library. The […]
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Introduction Seaborn is one of the most widely used data visualization libraries in Python, as an extension to Matplotlib. It offers a simple, intuitive, yet highly customizable API for data visualization. In this tutorial, we’ll take a look at how to plot a Violin Plot in Seaborn. Violin plots are used to visualize data distributions, displaying the range, median, and distribution of the data. Violin plots show the same summary statistics as box plots, but they also include Kernel Density […]
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Introduction Spelling mistakes are common, and most people are used to software indicating if a mistake was made. From autocorrect on our phones, to red underlining in text editors, spell checking is an essential feature for many different products. The first program to implement spell checking was written in 1971 for the DEC PDP-10. Called SPELL, it was capable of performing only simple comparisons of words and detecting one or two letter differences. As hardware and software advanced, so have […]
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Introduction Finding the right data we need is an age-old problem before computers. As developers, we create many search algorithms to retrieve data efficiently. Search algorithms can be divided into two broad categories: sequential and interval searches. Sequential searches check each element in a data structure. Interval searches check various points of the data (called intervals), reducing the time it takes to find an item, given a sorted dataset. In this article, you will cover Jump Search in Python – […]
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