Ensembling Techniques in Machine Learning

Ensembling Techniques in Machine Learning

We use various techniques to achieve greater accuracy in machine learning models. One such method is ensemble learning. In this article, we will discuss the basics of ensemble learning. We will discuss the various ensembling techniques and the differences between them. What is Ensemble Learning? Ensemble learning is a technique to build machine learning applications…

Naive Bayes Classification Numerical Example

We use different classification algorithms to build classifiers in machine learning. The naive Bayes classification algorithm is one of the easiest classification algorithms to understand and implement. In this article, we will discuss the Bayes algorithm and the intuition of Naive Bayes classification. We will also discuss a numerical example of Naive Bayes classification to…

Overfitting and Underfitting in Machine Learning

Overfitting and Underfitting are two of the common issues that we face while training machine learning models. In this article, we will discuss overfitting and underfitting in machine learning. We will also discuss how to avoid overfitting and underfitting using various techniques.  Before we start with a discussion on overfitting and underfitting, I suggest you…

Entity Embedding in Python

We often use categorical data encoding techniques such as label encoding and one hot encoding while data preprocessing. While these techniques offer an easy solution to convert categorical data to a numeric format, the representations are often inaccurate. In this article, we will discuss how to perform entity embedding to convert categorical data into a…

One Hot Encoding in Python

We use different categorical data encoding techniques while data analysis and machine learning tasks. In this article, we will discuss the basics of one hot encoding. We will also discuss implementing one hot encoding in Python. What is One Hot Encoding? One hot encoding is an encoding technique in which we represent categorical values with…

Implement Label Encoding in Python and PySpark

To analyze categorical data, we often need to convert them into numerical values. Label encoding is one of the most straightforward data preprocessing techniques for encoding categorical data into numeric values. This article will discuss different ways to perform label encoding in Python and pyspark. How to Perform Label Encoding? To perform label encoding, we…

Categorical Data Encoding Techniques Explained

To analyze categorical data, we need to convert them into numerical format. In this article, we will discuss different encoding techniques for converting categorical data into numeric format. How to Convert Categorical Data into Numerical Data? You can use the following encoding techniques to convert categorical into numeric data.  Let us discuss all the categorical…