Category: Python

Python tutorials

Advanced, NLP, Python, Social Media, Technique, Text, Unsupervised Leave a comment

Elon Musk AI Text Generator with LSTMs in Tensorflow 2

Introduction Elon Musk has become an internet sensation over the past couple of years, with his views about the future, funny personality along with his passion for technology. By now everyone knows him, either as that electric car guy, or that guy who builds flamethrowers. He is mostly active on his Twitter, where he shares everything, Even memes! He inspires a lot of young people in the IT industry, and I wanted to do a fun little project, where I […]

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Generating Synthetic Data with Numpy and Scikit-Learn

Introduction In this tutorial, we’ll discuss the details of generating different synthetic datasets using Numpy and Scikit-learn libraries. We’ll see how different samples can be generated from various distributions with known parameters. We’ll also discuss generating datasets for different purposes, such as regression, classification, and clustering. At the end we’ll see how we can generate a dataset that mimics the distribution of an existing dataset. The Need for Synthetic Data In data science, synthetic data plays a very important role. […]

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Python: Get Number of Elements in a List

Introduction Getting the number of elements in a list in Python is a common operation. For example, you will need to know how many elements the list has whenever you iterate through it. Remember that lists can have a combination of integers, floats, strings, booleans, other lists, etc. as their elements: # List of just integers list_a = [12, 5, 91, 18] # List of integers, floats, strings, booleans list_b = [4, 1.2, “hello world”, True] If we count the […]

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Beginner, Business Analytics, Infographic, Infographics, NLP, Python, Technique, Text, Unstructured Data Leave a comment

Quick Guide: Steps To Perform Text Data Cleaning in Python

Introduction Twitter has become an inevitable channel for brand management. It has compelled brands to become more responsive to their customers. On the other hand, the damage it would cause can’t be undone. The 140 character tweets has now become a powerful tool for customers / users to directly convey messages to brands. For companies, these tweets carry a lot of information like sentiment, engagement, reviews and features of its products and what not. However, mining these tweets isn’t easy. Why? Because, before you mine this data, you need […]

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Intermediate, Machine Learning, NLP, Programming, Python, Technique, Text, Unstructured Data Leave a comment

Introduction to Structuring Customer complaints explained with examples

Introduction In past, if you were not particularly happy with a service or a product, you would go to the service provider or the shop and lodge a complaint. With services-businesses going online and due to enormous scale, lodging complaints in-person may not be always possible. Electronic ways such as emails, social media and particularly websites like www.consumercomplaints.in focusing on such issues, are widely used platforms to vent out the anger as well as publicizing the issue in expectancy of […]

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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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Deep Learning, Intermediate, Listicle, NLP, Python, Technique Leave a comment

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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Intermediate, NLP, Project, Python, Sequence Modeling, Supervised, Text, Unstructured Data Leave a comment

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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Classification, Computer Vision, Deep Learning, Image, Libraries, NLP, Programming, Python, PyTorch, Supervised, Unstructured Data Leave a comment

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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