AI-ML Data Science

Understanding Naive Bayes using simple examples Thomas Bayes was an English statistician. As Stigler states, Thomas Bayes was born in […]

Decision Tree models are simple and easy to interpret. In this post, let us explore What are decision trees When

Heatmap depicts the two-dimensional data (matrix form) in the form of graph. Data requirement: Data can be in the form

Importing data into Python In this post, we will learn: How to import data into python How to import time

Train-Test split and Cross-validation Building an optimum model which neither underfits nor overfits the dataset takes effort. To know the

Occam’s Razor, Bias-Variance Tradeoff, No Free Lunch Theorem and The Curse of Dimensionality In this post, let us discuss some

“A picture is worth a thousand words” A complex idea can be understood effectively with the help of visual representations.

Scales of Measurement – Data types: Nominal, Ordinal, Interval and Ratio scale There are four measurement scales: Nominal Ordinal Interval

Autoregressive Integrated Moving Average (ARIMA) is a popular time series forecasting model. It is used in forecasting time series variable

Components of Time Series In this post, let us explore the four components of time series data. Trend (T) Cyclicality

Handling Missing Values in Python In this post, we will discuss: How to check for missing values Different methods to

Data Preprocessing – Creating Dummy Variables and Converting Ordinal Variables to Numbers with Examples Data cleaning is a critical step