Matplotlib Line Plot – Tutorial and Examples

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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Matplotlib Violin Plot – Tutorial and Examples

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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How to Upload Files with Python’s requests Library

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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Seaborn Violin Plot – Tutorial and Examples

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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Multilingualism in Natural Language Processing: Targeting Low Resource Indian Languages

Introduction A language is a systematic form of communication that can take a variety of forms. There are approximately 7,000 languages believed to be spoken across the globe. Despite this diversity, the majority of the world’s population speaks only a fraction of these languages. In Spite of such a rich diversity Languages are still evolving across time much like the society we live in. While the English language is uniform, having the distinct status of being the official language of […]

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Machine Translation Weekly 63: Maximum Aposteriori vs. Minimum Bayes Risk decoding

This week I will have a look at the best paper from this year’s COLING that brings an interesting view on inference in NMT models. The title of the paper is “Is MAP Decoding All You Need? The Inadequacy of the Mode in Neural Machine Translation” and its authors are from the University of Amsterdam. NMT models learn the conditional probability of the next word in a target sentence given the source sentence and the previous words in the target […]

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Multilingualism in Natural Language Processing targeting low resource Indian languages

Introduction Language is a systematic form of communication that can take a variety of forms. There are approximately 7,000 languages believed to be spoken across the globe. Despite this diversity, the majority of the world’s population speaks only a fraction of these languages. In Spite of such a rich diversity Languages are still evolving across time much like the society we live in. While the English language is uniform, having the distinct status of being the official language of multiple […]

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What Is Meta-Learning in Machine Learning?

Meta-learning in machine learning refers to learning algorithms that learn from other learning algorithms. Most commonly, this means the use of machine learning algorithms that learn how to best combine the predictions from other machine learning algorithms in the field of ensemble learning. Nevertheless, meta-learning might also refer to the manual process of model selecting and algorithm tuning performed by a practitioner on a machine learning project that modern automl algorithms seek to automate. It also refers to learning across […]

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Spelling Correction in Python with TextBlob

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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