Category: The Basics
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Linear Regression Fundamentals: Simple Linear Model, Part 2
Linear regression is a fundamental statistical technique to understand the relationship between two variables. It works on the principle of fitting a straight line through data points to model the relationship between the independent variable and the dependent variable(s).
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Book Review: Practical Statistics for Data Scientists
Bottom Line Up Front Statistics is essential for doing data science, but it is often not readily available or easily […]
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The Bias-Variance Trade-Off: Understanding the Balance in Models
What is the Bias-Variance Trade-Off The bias-variance tradeoff is a fundamental concept in machine learning that highlights the balance between […]
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Scraping with BeautifulSoup in Python: A Basic Guide
Basic process of using beautiful soup in python for web scraping.
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5 Essential Python Libraries for Data Science
If you’re diving into data science with Python, having the right tools in your toolkit is essential. Python’s ecosystem offers […]
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Linear Regression Fundamentals: Bridging Theory and Practice, Part 1
Linear regression is a fundamental statistical technique to understand the relationship between two continuous variables. It works on the principle […]
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Summary Statistics: the Essential Methods for Describing Data
use descriptive statistics and explore its significance in extracting valuable information from data.
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Exploring the Power of the Law of Large Numbers
What is it the Law of Large Numbers? In probability theory and statistics, the law of large numbers is a […]
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Mastering & Customizing Venn Diagrams in Python
A Venn diagram shows all possible logical relationships between a finite collection of different sets. Thankfully, creating Venn diagrams in […]
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Set Theory: Understanding the Basics
Definition What is a set? One may think of a set as a collection of objects. These objects can be […]