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Posts In Category "Data Analytics"

What is Data Mining: Definition, Purpose, and Techniques

A 2018 Forbes survey report says that most second-tier initiatives including data discovery, Data Mining/advanced algorithms, data storytelling, integration with operational processes, and enterprise and sales planning are very important to enterprises. To answer the question “what is Data Mining”, we may say Data Mining may be defined as the process of extracting useful information […]

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Are you looking for Spark Tutorial?

Apache Spark, more commonly known as Spark, has been adopted by enterprises across a wide range of industries. Internet powerhouses such as Netflix, Yahoo, and eBay have already deployed Spark, collectively processing multiple petabytes of data on clusters of over 8,000 nodes. Spark tutorial is becoming increasingly popular among developers across the world and has […]

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What is a Python Dictionary and How Does it Work?

Believe it or not, a Python dictionary works in a very similar way to a regular dictionary. Python offers many different data structures to hold information, and the dictionary is one of the simplest and most useful. While many things in Python are iterables, not all of them are sequences and a Python dictionary falls […]

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Central Limit Theorem: Everything You Need to Know

The Central Limit Theorem has a unique importance in the field of data science. In fact, many believe it’s one of the few theorems data scientists need to know. Although an early version of the Central Limit Theorem was discovered as far back as 1733 by Abraham de Moivre, it continues to be applied to […]

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The Complete Guide to Building an Ideal Data Scientist Resume

According to the LinkedIn Workforce Report for the US, there is a shortage of 151,717 data scientists across the United States. This shortage is not just restricted to the USA but is prevalent across the world, including in India. With so many positions available, data science does present great career opportunities. However, to get your […]

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Best Pandas Tutorials & What Makes Them Exceptional

The reason Python is the most popular language when it comes to data science and machine learning is its exceptional libraries. Pandas are one such Python library that is commonly used in data analysis. The Pandas library was created by Wes McKinney, founder of tech startup Datapad. While there is a lot of documentation around […]

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Regression Analysis: Everything You Need To Know

John Tukey once said, “An approximate answer to the right problem is worth a good deal more than an exact answer to an approximate problem.” That is exactly what regression analysis strives towards. It’s one of the most commonly used predictive modeling techniques that help make more informed decisions in important situations. In this article, […]

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Here’s What You Should Know About Logistic Regression

Logistic regression is an invaluable regression analysis technique in situations where linear regression simply cannot work. To quote prominent statistician Andy Field, “Logistic Regression is based on this principle: it expresses the multiple linear regression equation in logarithmic terms(called the logit) and thus overcomes the problem of violating the assumption of Linearity.” In this article, […]

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A-Z Guide to Linear Regression: Everything You Need to Know

Linear regression is one of the most common data analysis techniques to help you make sense of Big Data and enable more informed decision-making. This quote from renowned data scientist Tom Redman gives us the best possible explanation of linear regression. “Suppose you’re a sales manager trying to predict next month’s numbers. You know that […]

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Structural Equation Modeling: Definition and Analysis

Structural equation modeling is a statistical technique for testing and estimating causal relations using a combination of statistical data and qualitative causal assumptions. This definition of SEM was articulated by the geneticist Sewall Wright, the economist Trygve Haavelmo and the cognitive scientist Herbert A. Simon, and formally defined by Judea Pearl using a calculus of […]

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