Python tutorials

Simple NLP in Python With TextBlob: Tokenization

Introduction The amount of textual data on the Internet has significantly increased in the past decades. There’s no doubt that the processing of this amount of information must be automated, and the TextBlob package is one of the fairly simple ways to perform NLP – Natural Language Processing. It provides a simple API for diving into common natural language processing (NLP) tasks such as part-of-speech tagging, noun phrase extraction, tokenization, sentiment analysis, classification, translation, and more. No special technical prerequisites […]

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Add Legend to Figure in Matplotlib

Introduction Matplotlib is one of the most widely used data visualization libraries in Python. Typically, when visualizing more than one variable, you’ll want to add a legend to the plot, explaining what each variable represents. In this article, we’ll take a look at how to add a legend to a Matplotlib plot. Creating a Plot Let’s first create a simple plot with two variables: import matplotlib.pyplot as plt import numpy as np fig, ax = plt.subplots() x = np.arange(0, 10, […]

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The Essential NLP Guide for data scientists (with codes for top 10 common NLP tasks)

Introduction Organizations today deal with huge amount and wide variety of data – calls from customers, their emails, tweets, data from mobile applications and what not. It takes a lot of effort and time to make this data useful. One of the core skills in extracting information from text data is Natural Language Processing (NLP). Natural Language Processing (NLP) is the art and science which helps us extract information from text and use it in our computations and algorithms. Given […]

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A Guide to Building an Intelligent Chatbot for Slack using Dialogflow API

Introduction Breakthroughs in the field of Natural Language Processing (NLP) have seen a sudden rise in recent times. The amount of text data available to us is enormous, and data scientists are coming up with new and innovative solutions to parse through it and analyse patterns. From writing entire novels to decoding ancient texts, we have seen a variety of applications for NLP. One of the most popular applications is a chatbot. Organizations like Zomato, Starbucks, Lyft, and Spotify are leveraging […]

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Get Started with PyTorch – Learn How to Build Quick & Accurate Neural Networks (with 4 Case Studies!)

Introduction PyTorch v TensorFlow – how many times have you seen this polarizing question pop up on social media? The rise of deep learning in recent times has been fuelled by the popularity of these frameworks. There are staunch supporters of both, but a clear winner has started to emerge in the last year. PyTorch was one of the most popular frameworks in 2018. It quickly became the preferred go-to deep learning framework among researchers in both academia and the […]

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Predicting Movie Genres using NLP – An Awesome Introduction to Multi-Label Classification

Introduction I was intrigued going through this amazing article on building a multi-label image classification model last week. The data scientist in me started exploring possibilities of transforming this idea into a Natural Language Processing (NLP) problem. That article showcases computer vision techniques to predict a movie’s genre. So I had to find a way to convert that problem statement into text-based data. Now, most NLP tutorials look at solving single-label classification challenges (when there’s only one label per observation). […]

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10 Powerful Applications of Linear Algebra in Data Science (with Multiple Resources)

Overview Linear algebra powers various and diverse data science algorithms and applications Here, we present 10 such applications where linear algebra will help you become a better data scientist We have categorized these applications into various fields – Basic Machine Learning, Dimensionality Reduction, Natural Language Processing, and Computer Vision   Introduction If Data Science was Batman, Linear Algebra would be Robin. This faithful sidekick is often ignored. But in reality, it powers major areas of Data Science including the hot […]

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Build Your First Text Classification model using PyTorch

Overview Learn how to perform text classification using PyTorch Grasp the importance of Pack Padding feature Understand the key points involved while solving text classification Introduction I always turn to State of the Art architectures to make my first submission in data science hackathons. Implementing the State of the Art architectures has become quite easy thanks to deep learning frameworks such as PyTorch, Keras, and TensorFlow. These frameworks provide an easy way to implement complex model architectures and algorithms with […]

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Machine Learning in Cyber Security — Malicious Software Installation

Introduction Monitoring of user activities performed by local administrators is always a challenge for SOC analysts and security professionals. Most of the security framework will recommend the implementation of a whitelist mechanism. However, the real world is often not ideal. You will always have different developers or users having local administrator rights to bypass controls specified. Is there a way to monitor the local administrator activities?

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Save Plot as Image with Matplotlib

Introduction Matplotlib is one of the most widely used data visualization libraries in Python. It’s common to share Matplotlib plots and visualizations with others. In this article, we’ll take a look at how to save a plot/graph as an image file using Matplotlib. Creating a Plot Let’s first create a simple plot: import matplotlib.pyplot as plt import numpy as np x = np.arange(0, 10, 0.1) y = np.sin(x) plt.plot(x, y) plt.show() Here, we’ve plotted a sine function, starting at 0 […]

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