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The A-Z guide to Support Vector Machine
Learn the fundamentals of Support Vector Machine with our beginner's guide, perfect for those new to this powerful machine learning model.Start Reading Now!
Premanand S 16 Nov, 2023
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Descriptive Statistics: Definitions, Types and Examples
Discover descriptive statistics & its types. Learn about central tendency, data dispersion, and how to analyze univariate vs. bivariate data.
Illiyas 07 Apr, 2025
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Getting Started with Machine Learning - Implementing Linear Regression from Scratch
In this blog, we will be implementing one of the most basic algorithms in machine learning i.e Simple Linear Regression in python. Explore ML Today!
Yashowardhan 01 Dec, 2023
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Traversing the Trinity of Statistical Inference Part 1: Estimation
An estimator is a statistic that does not depend upon the true parameter. It’s a statistic/estimation, means, it’s a measurable function of the sample
Naman 15 Jun, 2021
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Crowd Counting using Deep Learning
Crowd counting is prominent in the various object counting tasks due to its specific significance to social security & development
Yash 14 Jun, 2021
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Recurrent Neural Networks : Introduction for Beginners
Recurrent neural networks is a type of neural network in which the output form the previous step is fed as input to the current step
Aman 13 Jun, 2021
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Decoding the Chi-Square Test - Use along with Implementation and Visualization
Learn the Chi-Square Test to find correlations b/w categorical variables in Python, including implementation and visualization techniques.
Yashowardhan 28 Jan, 2025
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Complete Guide to Chebyshev’s Inequality and WLLN in Statistics for Data Science
Chebyshev’s inequality and Weak law of large numbers (WLNN) in statistics are very important concepts that are heavily used in DS.
Aashi 08 Jun, 2021
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Parametric and Non-Parametric Tests: The Complete Guide
Learn about parametric and non-parametric tests, their importance, differences, and various types like T-Test, Z-Test, ANOVA, Chi-Square Test.
Aashi 04 Apr, 2025
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How does Backward Propagation Work in Neural Networks?
Backward propagation is a process of moving from the Output to the Input layer. Learn the working of backward propagation in neural networks.
Neha 08 Jun, 2021
