Hello Professionals !!
Welcome to today’s edition of BUSINESS ANALYTICS REVIEW ! We hope you enjoyed our previous newsletter on AI driven Analytics.
Today, we’re diving into the world of Natural Language Processing (NLP), a revolutionary technique that's reshaping how businesses comprehend and leverage textual data.
What is NLP ? NLP is a branch of artificial intelligence that enables computers to interpret, analyze, and even generate human language. From chatbots to sentiment analysis, NLP has found its way into almost every industry, helping businesses make sense of unstructured data, particularly textual information.
Why is NLP Important for Business Analytics?
Sentiment Analysis
NLP can analyze text from reviews and social media to detect positive, negative, or neutral sentiments. This helps companies gauge customer satisfaction, identify areas for improvement, and stay on top of public opinion.Text Classification
NLP techniques can automatically categorize text into predefined topics. For instance, customer service inquiries can be grouped into different categories, making it easier for companies to respond quickly and efficiently.Topic Modeling
NLP can also uncover hidden themes in large datasets. By clustering similar words and phrases, it identifies patterns or topics within your data. This is especially useful for market research and product development.
Key Techniques in NLP:
Tokenization
This is the process of splitting text into individual words or phrases (tokens). It helps to break down language into manageable chunks, which is essential for most NLP tasks like text classification or translation.Sentiment Analysis
This is used to detect the tone or sentiment behind a body of text. Companies use it to gauge customer opinions on products, with reviews or social media posts.Named Entity Recognition (NER)
NER identifies entities such as names, locations, and organizations in text. It’s key in information extraction tasks.Text Classification
NLP can automatically categorize text into predefined categories, such as spam filtering or sorting customer feedback.
In our last email we talked about AI Driven Analytics please read here Or search ‘businessanalytics@substack.com’ in your mailbox.
Recommended Articles on NLP:
Natural Language Processing (NLP): A Beginner's Guide : This comprehensive guide introduces the basics of NLP, covering key concepts, techniques, and applications. It's a great starting point for those new to the field.
Read HereNLP Tools and Libraries: A Comparison by KD Nuggets : This article compares popular NLP tools and libraries like NLTK, spaCy, and Gensim, helping you choose the best fit for your specific needs.
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Latest Insights and Trends in Business Analytics
US-based data analytics firm FICO launches its cloud platform in India. Indian banks like HDFC Bank, Axis Bank, and AU Small Finance Bank are among the early adopters set to elevate customer satisfaction and drive innovation in the banking sector.
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According to a report by analytics firm Similarweb, ChatGPT OpenAI's highly popular artificial intelligence (AI) tool saw a third consecutive monthly decrease in website traffic during August. There are also indications that this decline could be stabilising, according to Reuters.
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Two Artificial Intelligence (AI) Stocks to Buy With $1,000 and Hold for Decades. Oracle Chairman Larry Ellison offered investors some fresh insights into the current state of artificial intelligence (AI). He said there was no slowdown in sight in terms of business spending on the development of AI. Indeed, he thinks the industry will expand significantly for at least the next 10 years.
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Tool of the Day: Stanford CoreNLP
Stanford CoreNLP is a comprehensive suite of natural language processing (NLP) tools developed by the Stanford Natural Language Processing Group. It offers a wide range of functionalities, making it a valuable resource for researchers, developers, and businesses.
Stanford CoreNLP is widely used in various NLP applications, including:Text summarization, Machine translation, Question answering, Chatbots, Information extraction.
Like this edition below & we’d love to hear your thoughts in the comments below—what’s your favourite NLP application?
Stay tuned for our next issue on Big Data Management!