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AI-ML-DS / Machine Learning

Machine Learning

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LightGBM for Quantile Regression

Last Updated: 06 June 2025

In most machine learning problems, we try to predict the average or expected value of a target variable. For example, if we want to predict the price of a house we usually...read more

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Machine Learning

LightGBM Key Hyperparameters

Last Updated: 06 June 2025

LightGBM is a popular machine learning algorithm used for solving classification and regression problems. It is known for its speed and accuracy and it is especially good ...read more

Machine Learning

Reducible Error vs Irreducible Error in Machine Learning

Last Updated: 27 May 2025

There are two types of errors in machine learning model. They are reducible and irreducible error. We cannot reduce the irreducible error as it is caused by factors that a...read more

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Machine Learning

Machine Learning

AI-ML-DS With Python

What is Residual Standard Error

Last Updated: 30 May 2025

Residual Standard Error (RSE) is a measure of the quality of a linear regression model. It shows how much the observed values deviate from the predicted values. In simpler...read more

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Machine Learning

AI-ML-DS With Python

What is Specificity

Last Updated: 02 June 2025

Specificity is important to check how well a model can correctly find negative cases. It is useful when making a wrong positive prediction (false positive) causes big prob...read more

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Machine Learning

Bayes Classification

Last Updated: 03 June 2025

Bayes Classification is a Supervised machine learning approach for classification. It works on a probabilistic method which uses Bayes Theorem to be implemented. It predic...read more

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Machine Learning

Machine Learning

What is Data Imputation

Last Updated: 30 May 2025

Data Imputation is the process of handling missing values or null values in a dataset for the purpose of enhancing efficiency and accuracy in the model training process. T...read more

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Machine Learning

AI-ML-DS With Python

Rolling Regression

Last Updated: 31 May 2025

Rolling Regression is a type of Linear Regression model that is used for analyzing changing relationships among variables over time. It uses a statistical iterative appro...read more

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Machine Learning

AI-ML-DS With Python

What is Adversarial Machine Learning?

Last Updated: 02 June 2025

Adversarial machine learning (AML) is refers to machine learning threats which aims to trick machine learning models by providing deceptive input. Such attacks force the m...read more

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Machine Learning

False Positive Rate

Last Updated: 31 May 2025

False Positive Rate (FPR) refers to the metric to calculate the percentage of incorrect positive predictions made by a machine learning algorithm. It is measured by compar...read more

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Machine Learning

AI-ML-DS With Python

Hard or Soft Classification

Last Updated: 02 June 2025

In the field of machine learning, classification is a core task where models are trained to assign input data into predefined categories. Depending on the nature of the ta...read more

Machine Learning

Macro average vs Weighted average

Last Updated: 09 June 2025

Weighted Average and Macro Average are two methods commonly used to evaluate model performance in multi-class and imbalanced classification problems. In such scenarios whe...read more

Machine Learning

Conformal Inference

Last Updated: 09 June 2025

Conformal inference provides a statistically sound and practical solution to the growing need for trustworthy AI in critical applications. In high stakes decisions such as...read more

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Machine Learning

Knowledge Distillation

Last Updated: 06 June 2025

Knowledge Distillation is a model compression technique in which a smaller, simpler model (student) is trained to imitate the behavior of a larger, complex model (teacher)...read more

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Machine Learning

AI-ML-DS With Python

Unbiased Estimator

Last Updated: 09 June 2025

An unbiased estimator is a statistical estimator whose expected value is equal to the true value of the parameter being estimated. In simple words, it produces correct res...read more

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Machine Learning

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