Ultimate Guide to Understand and Implement Natural Language Processing (with codes in Python)

Overview Complete guide on natural language processing (NLP) in Python Learn various techniques for implementing NLP including parsing & text processing Understand how to use NLP for text feature engineering   Introduction According to industry estimates, only 21% of the available data is present in structured form. Data is being generated as we speak, as we tweet, as we send messages on Whatsapp and in various other activities. Majority of this data exists in the textual form, which is highly unstructured […]

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Ultimate guide to deal with Text Data (using Python) – for Data Scientists and Engineers

Introduction One of the biggest breakthroughs required for achieving any level of artificial intelligence is to have machines which can process text data. Thankfully, the amount of text data being generated in this universe has exploded exponentially in the last few years. It has become imperative for an organization to have a structure in place to mine actionable insights from the text being generated. From social media analytics to risk management and cybercrime protection, dealing with text data has never […]

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Comprehensive Hands on Guide to Twitter Sentiment Analysis with dataset and code

Introduction Natural Language Processing (NLP) is a hotbed of research in data science these days and one of the most common applications of NLP is sentiment analysis. From opinion polls to creating entire marketing strategies, this domain has completely reshaped the way businesses work, which is why this is an area every data scientist must be familiar with. Thousands of text documents can be processed for sentiment (and other features including named entities, topics, themes, etc.) in seconds, compared to […]

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Steps for effective text data cleaning (with case study using Python)

Introduction   The days when one would get data in tabulated spreadsheets are truly behind us. A moment of silence for the data residing in the spreadsheet pockets. Today, more than 80% of the data is unstructured – it is either present in data silos or scattered around the digital archives. Data is being produced as we speak – from every conversation we make in the social media to every content generated from news sources. In order to produce any […]

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Beginners Guide to Topic Modeling in Python

Introduction Analytics Industry is all about obtaining the “Information” from the data. With the growing amount of data in recent years, that too mostly unstructured, it’s difficult to obtain the relevant and desired information. But, technology has developed some powerful methods which can be used to mine through the data and fetch the information that we are looking for. One such technique in the field of text mining is Topic Modelling. As the name suggests, it is a process to […]

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Natural Language Processing for Beginners: Using TextBlob

Introduction Natural Language Processing (NLP) is an area of growing attention due to increasing number of applications like chatbots, machine translation etc. In some ways, the entire revolution of intelligent machines in based on the ability to understand and interact with humans. I have been exploring NLP for some time now.  My journey started with NLTK library in Python, which was the recommended library to get started at that time. NLTK is a perfect library for education and research, it becomes […]

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NLP Essentials: Removing Stopwords and Performing Text Normalization using NLTK and spaCy in Python

Overview Learn how to remove stopwords and perform text normalization in Python – an essential Natural Language Processing (NLP) read We will explore the different methods to remove stopwords as well as talk about text normalization techniques like stemming and lemmatization Put your theory into practice by performing stopwords removal and text normalization in Python using the popular NLTK, spaCy and Gensim libraries   Introduction Don’t you love how wonderfully diverse Natural Language Processing (NLP) is? Things we never imagined […]

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FlashText – A library faster than Regular Expressions for NLP tasks

People like me working in the field of Natural Language Processing almost always come across the task of replacing words in a text. The reasons behind replacing the words may be different. Some of them are. “would’ve” and “would have” represent the same thing. So changing all the occurrences of “would’ve” to “would have” is one such task. Changing all Case Variations to a single form i.e Python, pytHon, pYthon, pythoN etc. to python Changing all the synonyms of a word to […]

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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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Beginners Tutorial for Regular Expressions in Python

Importance of Regular Expressions In last few years, there has been a dramatic shift in usage of general purpose programming languages for data science and machine learning. This was not always the case – a decade back this thought would have met a lot of skeptic eyes! This means that more people / organizations are using tools like Python / JavaScript for solving their data needs. This is where Regular Expressions become super useful. Regular expressions are normally the default way […]

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