Programming: Jupyter, Python, Django and Git
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Jupyter Notebook for Beginners: A Tutorial
The Jupyter Notebook is an incredibly powerful tool for interactively developing and presenting data science projects. This article will walk you through how to set up Jupyter Notebooks on your local machine and how to start using it to do data science projects.
First, though: what is a “notebook”? A notebook integrates code and its output into a single document that combines visualizations, narrative text, mathematical equations, and other rich media. This intuitive workflow promotes iterative and rapid development, making notebooks an increasingly popular choice at the heart of contemporary data science, analysis, and increasingly science at large.
Best of all, as part of the open source Project Jupyter, they are completely free.
The Jupyter project is the successor to the earlier IPython Notebook, which was first published as a prototype in 2010. Although it is possible to use many different programming languages within Jupyter Notebooks, this article will focus on Python as it is the most common use case. (Among R users, R Studio tends to be a more popular choice).
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Python for NLP: Creating Multi-Data-Type Classification Models with Keras
This is the 18th article in my series of articles on Python for NLP. In my previous article, I explained how to create a deep learning-based movie sentiment analysis model using Python's Keras library. In that article, we saw how we can perform sentiment analysis of user reviews regarding different movies on IMDB. We used the text of the review the review to predict the sentiment.
However, in text classification tasks, we can also make use of the non-textual information to classify the text. For instance, gender may have an impact on the sentiment of the review. Furthermore, nationalities may affect the public opinion about a particular movie. Therefore, this associated info, also known as meta data can also be used to improve accuracy of statistical model.
In this article, we will build upon the concepts that we studied in the last two articles and will see how to create a text classification system that classifies user reviews regarding different business, into one of the three predefined categories i.e. "good", "bad", and "average". However, in addition to the text of the review, we will use the associated meta data of the review to perform classifcation. Since we have two different types of inputs i.e. textual input and numerical input, we need to create a multiple inputs model. We will be using Keras Functional API since it supports multiple inputs and multiple output models.
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Django Template Fiddle Launched !!!!
This is not an article. We just want to inform you that we have launched our new platform where you can experiment, play or fiddle with Django Templates.
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Python Script 16: Generating word cloud image of a text using python
Word cloud is an image composed of words used in a particular text or subject, in which the size of each word indicates its frequency or importance.
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Python 3.7.3 : Using the inotify.
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Git is eating the world
The inception of Git (2005) is more or less the halfway point between the inception of Linux (1991) and today (2019). A lot has happened since. One thing is clear however: software is eating the world and Git is the fork with which it is being eaten. (Yes, pun intended).
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Dilution and Misuse of the "Linux" Brand
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