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Top 5 Statistical Concepts Every Data Scientist Should Know in 2020!
Statistical concepts help us derive better insights about the data abd help us reach better conclusions. Here are my favorite concepts.
pavan 25 Nov, 2020
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A Primer on Getting Started with Data Science for Beginners
This article is a primer on getting started with Data Science. We will discuss how to learn and retain concepts of data science for beginners
Abhishek 08 Dec, 2020
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A Definitive Guide for predicting Customer Lifetime Value (CLV)
Let's predict customer lifetime value which is the total monetary value of purchases made by a customer with your business over his lifetime
Hariharan 15 Oct, 2024
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A/B Testing for Data Science using Python – A Must-Read Guide for Data Scientists
A/B Testing is a way to test your products. In this article learn what is A/b testing in data science and how data scientists leverage it.
Shipra Saxena 10 Jan, 2025
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Demystification of Logistic Regression
In this article we are going to understand the basics of Logistic Regression and demistify for you the mathematics behind it.
Neha 23 Nov, 2020
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Quick Guide to Evaluation Metrics for Supervised and Unsupervised Machine Learning
Enhance your Data Science skills with ML evaluation metrics. From rand index to calinski-harabasz Index and mutual info for accuracy.
Manish 18 Jul, 2024
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How to Choose Evaluation Metrics for Classification Models
In this article, let us deep dive into the most common evaluation metrics for classification models that all data scientists should know
Muskan 11 Oct, 2020
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Complete R Tutorial To Build Probabilistic Graphical Models!
Probabilistic Graphical Models (PGM) capture the complex relationships between random variables to build an innate structure.
Vidhi 09 Oct, 2020
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A Quick Guide to Descriptive Statistical Analysis – The First Step in Exploring your Data
Descriptive Statistics is the default process in Data analysis. Here is a quick guide to descriptive statistical analysis.
manmohannov 24 Oct, 2024
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How Machine Learning Models Fail to Deliver in Real-World Scenarios
Machine learning models fail in the real world but a lot of people don't know why. Here's an explanation where you can understand why.
Eshan 05 Oct, 2020
