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9 important plots in data science

Data Science Dojo

Learn about 33 tools to visualize data with this blog In this blog post, we will delve into some of the most important plots and concepts that are indispensable for any data scientist. 9 Data Science Plots – Data Science Dojo 1. Suppose you are a data scientist working for an e-commerce company.

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Hellinger distance

Dataconomy

By providing a clear numerical representation of similarity, Hellinger Distance aids researchers and data scientists in understanding and analyzing complex problems with ease. In statistics: – Utilized for hypothesis testing to assess the validity of statistical models. What is Hellinger distance?

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Unlocking data science 101: The essential elements of statistics, Python, models, and more

Data Science Dojo

Statistics: Unveiling the patterns within data Statistics serves as the bedrock of data science, providing the tools and techniques to collect, analyze, and interpret data. It equips data scientists with the means to uncover patterns, trends, and relationships hidden within complex datasets.

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Introduction to applied data science 101: Key concepts and methodologies 

Data Science Dojo

Statistical analysis and hypothesis testing Statistical methods provide powerful tools for understanding data. An Applied Data Scientist must have a solid understanding of statistics to interpret data correctly. Machine learning algorithms Machine learning forms the core of Applied Data Science.

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Data Scientist Salary in India’s Top Tech Cities

Pickl AI

A Data Scientist’s average salary in India is up to₹ 8.0 Well, one of the key factors drawing attention towards the Data Scientist job profile is the higher pay package. In fact, the highest salary of a Data Scientist in India can be up to ₹ 26.0 Data Scientist Salary in Hyderabad : ₹ 8.0

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Data Science skills: Mastering the essentials for success

Pickl AI

Summary: The role of a Data Scientist has emerged as one of the most coveted and lucrative professions across industries. Combining a blend of technical and non-technical skills, a Data Scientist navigates through vast datasets, extracting valuable insights that drive strategic decisions.

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Introduction to R Programming For Data Science

Pickl AI

R’s data manipulation capabilities make cleaning and preprocessing data easy before further analysis. · Statistical Analysis: R has a rich ecosystem of packages for statistical analysis. Packages like tidyverse, knitr, and shiny offer a cohesive data import, cleaning, analysis, visualization, and reporting ecosystem.