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Posts In Category "Data Science"

Top Data Science Institutes in Mumbai: 2020 Review

Digital Vidya is one of the best Data Science institutes in Mumbai. It focuses on producing job-ready professional data scientists. Today, almost every industry, domain, and organization uses data science to help their businesses grow and adapt to the demands of the customers. It has been named the number one job in the U.S by […]

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A Comprehensive Guide to Learning Text Classification

In this article, we shall examine what text classification is and understand its significance. We live in a fast-paced age where no one has time to read an entire message. Usually, one glances through emails and other communication to get the gist of the matter. It can be challenging to capture the central idea of […]

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A Comprehensive Guide to Data Manipulation for Experts and Beginners

Data manipulation is an integral aspect of data science. Data needs to be structured for enabling machines to read it. However, it needs manipulation for humans to use it. As the amount of data being used and storage increases day by day, data manipulation becomes more critical than ever. Don Henley had once stated, There […]

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How to Build a Career in Data Science with Some Simple Steps

It’s hard to think of something that has nothing to do with data and information. Experts predict that 40 zettabytes of data will be in existence by 2020. Consequently, a career in data science will present opportunities that will shoot through the roof! A report by Glassdoor, a website where current and former employees anonymously […]

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A-Z of Inferential Statistics

One of the essential skills that a Data Scientist needs is that of statistics, both descriptive and inferential statistics. Through the power of mathematical statistics, it is possible to predict possible outcomes and judge current market trends. Take descriptive and inferential statistics, for example. While descriptive statistics help in describing data, inferential statistics help in […]

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All You Need to Know About Collaborative Filtering

Before we get into core concepts like collaborative filtering recommender systems and collaborative filtering algorithms, let’s understand recommender systems. A recommender system aims to predict a user’s preference, in order to ‘recommend’ an item, that could be a product like clothes, or could be movies, services, etc., recommender systems have become very important today because […]

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Complete Guide to Naive Bayes Classifier

A classifier, in machine learning, is a model or algorithm used to differentiate between objects based on specific features. Naive Bayes Classifiers come under this family of classifiers (probabilistic classifiers to be exact). The naive Bayes classifier is based on the application of Bayes’ theorem with strong (hence the word naive) independence assumptions between the […]

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Ultimate Principal Component Analysis Tutorial

Principal Component Analysis, or PCA, is a statistical procedure that essentially involves coordinate transformation. It involves the orthogonal transformation of possibly correlated variables into a set of linearly uncorrelated variables called principal components. If the original data is plotted on an X and Y axis, the principal component analysis will modify these axes so that […]

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The Ultimate Guide to Learning Sentiment Analysis

Sentiment analysis, also known as ‘opinion mining’, is basically the process of identifying the emotions or emotional tone behind a series of words by using Artificial Intelligence. Sentiment analysis helps analysts understand the current emotion, opinion or attitude of the general population behind a certain topic or set of words mentioned online. Understanding the current […]

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The Ultimate Guide To Bayesian Network

In this guide, we shall explain the Bayesian Network. Bayesian networks are all about probability and statistics. When you talk of probability, this funny definition of probability comes to mind. “The probability of meeting someone you know becomes higher when you are with someone you are not supposed to be seen with.” A Bayesian network […]

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