Data Science

Fixed vs Random vs Mixed Effects Models – Examples

Have you ever wondered what fixed effect, random effect and mixed effects models are? Or, more importantly, how they differ…

2 years ago

CNN Basic Architecture for Classification & Segmentation

As data scientists, we are constantly exploring new techniques and algorithms to improve the accuracy and efficiency of our models.…

2 years ago

Neural Network & Multi-layer Perceptron Examples

Neural networks are an important part of machine learning, so it is essential to understand how they work. A neural…

2 years ago

Positively Skewed Probability Distributions: Examples

Probability distributions are an essential concept in statistics and data analysis. They describe the likelihood of different outcomes or events…

2 years ago

Generative vs Discriminative Models: Examples

The field of machine learning is rapidly evolving, and with it, the concepts and techniques that are used to develop…

2 years ago

Sequence to Sequence Models: Types, Examples

Sequence to sequence (Seq2Seq) modeling is a powerful machine learning technique that has revolutionized the way we do natural language…

2 years ago

Statistics Terminologies Cheat Sheet & Examples

Have you ever felt overwhelmed by all the statistics terminology out there? From sampling distribution to central limit theorem to…

2 years ago

Machine Learning Bias Explained with Examples

In the artificial intelligence (AI) / machine learning (ML) powered world where predictive models have started getting used more often…

2 years ago

Geometric Distribution Concepts, Formula, Examples

Geometric Distribution, a widely used concept in probability theory, is used to represent the probability of achieving success or failure…

2 years ago

Data value chain: Framework, Concepts

As organizations become increasingly data-driven, understanding the value of data is critical for success. The data value chain framework helps…

2 years ago