Data Science has become one of the most interesting and most sought jobs in recent times. While the demand for the job has become quite competitive, the job seekers still find themselves in bewilderment as there is no right guide for cracking the data science interviews. In this article, we aim towards providing our readers
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“India is today among the top 10 destinations for analytics and our aspiration is to be among the top three in the world by 2025"
These golden lines by the NASSCOM vice-president KS Viswanathan in 2016 showed everyone the potential of India and its people in the field of analytics. It not only motivated us with
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Undoubtedly, data science has taken down most industries, making data scientists the most sought job of the 21st century as per the Harvard business review. Despite the increasing demand and appetite for experienced data scientists, the job is ambiguously described most of its time. This lack of real industry-standard still confuses a lot of professionals
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Big data is a field that deals with data sets that are too large or too complex to be dealt with data-processing application software. Only experienced people work on Big Data is one of the biggest fallacies. Whether it is an old technology like mainframes or something latest as Big Data, there is no such
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“I had the idea of learning about data science, and that’s what brought me to Ivy”. Arpita Ghosh, our student from Ivy Pro School, completed her master’s graduation in 2019. She has been excelling in the market research industry since then. Learning about data science and its real-life application was very intriguing for her. Thus
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Data Science has become one of the most interesting jobs in recent times. While the demand for the job has become quite competitive, the job seekers still find themselves in bewilderment as there is no right guide for cracking the data science interview.
In this article, we aim towards providing our readers with proper information about
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Business Analytics is often misunderstood with Data Analytics and the sole reason for this article is to bust this myth and educate our avid readers about the exact role of an individual pursuing a career in business analytics.
Definition: What is Business Analytics?
Business Analytics is a process that is carried out to understand business performance, gain
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We have learned several string operations in our previous blogs. Proceeding further we are going to work on some very interesting and useful concepts of text preprocessing using NLTK in Python. Let us first understand the text processing thought process by observing the following text to work on.
sample_text = '''A nuclear power plant is a
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Data Science, Machine Learning, Artificial Intelligence, Automation, etc. technologies gained a lot of attention in the recent past. More so because of the potential to help businesses with their applications and beneficial use cases. Consequently, businesses globally from every industry started to pick up these technologies at a very fast rate. According to a report,
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This article is in continuation of our first part of a Step by Step guide of Python Regular Expressions. The meta-characters, special sequences, and sets are the essential parts of a regular expression. We are going to talk about working examples of these on the two-sample text data considered earlier. The movie review text is
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Introduction -
Would not that be surprising if someone says he or she is not aware of Facebook? Undoubtedly, a majority of us most likely uses this social media platform for a while every day. As of December 2019, Facebook has got 2.5 billion active users monthly. This might just be an exciting fact for common
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The very first article in the NLP series introduced Natural Language Processing. We then explained String Operations that can be performed on text using Python. Further, in the quest to strengthen our text pre-processing, we must have a good understanding of Regular Expressions. This article is the first part of a step by step guide
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Hello NLP learner!! I hope you had visited our last article - Introduction to Natural Language Processing using Python. With that, you would have got an idea that Natural Language Processing essentially deals with Text Analytics. As a next step, we naturally need to learn how to deal with text or in other words strings
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Chatbots are a common feature on any website these days. We visit a site, and a chatbot pops up encouraging us to interact. Many of us will find this intriguing. A Data Science enthusiast will probably go ahead and look for the underlying concept of Natural Language Processing (NLP). I have recently done a lot
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We all know that the world recently took a massive hit from the COVID-19 pandemic, which continues to spread at a scary fast speed. As they say that "Desperate times need desperate measures". The "Lockdown" strategy was decided upon as a measure to contain its outspread. Consequently, and instantly, the global economy went far south.
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Introduction -
Data Visualization is necessary and indeed a very interesting scope of work while solving any Data Science problem. There are several licensed and open-source Data Visualization tools available in the market like Tableau, Power BI, DataWrapper, Infogram, etc. Having said that, Python is in no way behind and provides some amazing libraries to perform
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