Statistics & Probability
Statistics and probability are the best tools for solving problems, whether they are real-world problems or optimising machine learning models. Making sense of data and extracting meaningful information from it using statistical techniques, formulas, and variable moderation is an important first step in working on machine learning or deep learning systems.
Introduction to statistics
By aniket verma
● Published At Dec 2021
The objective of this blog is to give an introduction to statistics and its importance in ML.... Keep reading ..
Scales of Measurement
By Mohammad Yawar
● Published At May 2022
This article talks about the different scales of measurement ... Keep reading ..
Variance and standard deviation
By Pradipta Choudhury
● Published At May 2022
This article begins with an introduction to variance and standard deviation, how to calculate them, and their implementation in python.... Keep reading ..
Skewness and Kurtosis
By Mayank Goyal
● Published At Jan 2022
This article will study two statistical concepts,i.e., Skewness and kurtosis, and their applications.... Keep reading ..
Combinatorics for ML
By Mohammad Yawar
● Published At Jun 2022
This blog talks about combinatorics method and its application in Machine learning.... Keep reading ..
Categorical Data
Categorical data is a subtype of data that is commonly discovered while extracting and working with datasets. The categorical data is made up of various divided categories that can include both numbers and characters.
Categorical Data  - Intro & Hands-On
By soham Medewar
● Published At Mar 2022
In this article, we will discuss categorical data, and operations on it.... Keep reading ..
Categorical Data - Measure of Central Tendency
By Mayank Goyal
● Published At Jan 2022
This article will study categorical data and measure its central tendency.... Keep reading ..
Numerical Data
Another type of data that is commonly found is numerical data, which consists primarily of numbers. It focuses on quantitative data collection. It is very simple to perform various mathematical operations on numerical data and to easily analyse the data.
Numerical Data - Measure of Central Tendency
By Mayank Goyal
● Published At Jan 2022
In this article, we will discuss measures of central tendency. We will see the visualization and code implementation for all the measures of central tendencies.... Keep reading ..
Numerical Data - Measure of Dispersion
By soham Medewar
● Published At Jan 2022
In this article, we will discuss measures of dispersion and their types in numerical data. Visualization and code implementation for all the measures of dispersion.... Keep reading ..
Probability
Probability is another important mathematical aspect that is usually required for data analysis, algorithm optimization, and model optimization. This domain is useful for dealing with data that has a lot of variables and performing operations on it.
Discrete and Continuous Random Variable
Variables that are commonly used in probability operations and are the result of measurement.
Multiple Random Variable
Multiple random variables, also known as multivariate random variables, are variables with undetermined values that play an important role in probabil
Introduction to Random Variables
By Mandla Dharani
● Published At Mar 2022
In this blog, we discussed an introduction to random variables, followed by their types and applications. ... Keep reading ..
Bayesian Estimation
By Arun Nawani
● Published At Mar 2022
The blog gives an insight into a popular parameter optimisation technique known as Bayesian Estimation. ... Keep reading ..
Maximum Likelihood Estimation vs Bayesian Estimation
By Arun Nawani
● Published At May 2022
The blog lists key differences between Maximum Likelihood Estimation and Bayesian Estimation.... Keep reading ..
Hypothesis Testing
By Mayank Goyal
● Published At Jan 2022
This article focuses on hypothesis testing, various techniques, and their implementation.... Keep reading ..
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