- Introduction
- How does KNN work?
- Euclidean Distance
- Manhattan Distance
- KNN with the imbalanced dataset.
- Lazy Learners.
- Advantages and disadvantages.

K-nearest neighbor (KNN) is one of the most important supervised machine learning algorithms. It is used for both classifications as well as a regression problem. It is used to classify the…

Machine Learning Algorithms — **Linear Regression in Hindi** — Is post me hum bat Karne wale hai linear regression k bare me. Jab bhi hum machine learning ke algorithms ko padhna start karte hai to hum start linear regression algorithm ke saath karte hai. …

Machine learning is a technique of building a model by using different techniques and algorithms. Here I am not going to discuss the detail of machine learning. we will learn about the random forest algorithm of machine learning. …

*This article was published as a part of the **Data Science Blogathon**.*

K-means clustering is a very famous and powerful unsupervised machine learning algorithm. It is used to solve many complex unsupervised machine learning problems. …

Adaboost is also known as *Adaptive Boosting. *It is the first boosting algorithm that every machine learning enthusiast learns. This post is going to explain the in-depth explanation of AdaBoost and also the maths behind this algorithm. Now let’s start with the introduction of AdaBoost.

- AdaBoost is the ensemble learning…

A decision tree is a very important supervised learning technique. It is basically a classification problem. It is a tree-shaped diagram that is used to represent the course of action. It contains the nodes and leaf nodes. it uses these nodes and leaf nodes to draw the conclusion. Here we…

Whenever we start our journey into the Machine Learning, linear regression is the first basic algorithm which we study into the regression problem. It is a very straightforward, easy but very important algorithm. So let’s see what this linear regression is?

*“The linear regression algorithm establishes the relationship between the…*

Everyone used to hear about the credit risk in his daily life, especially people who are working in finance, banking, or people who are working as a business analyst. So what is this *credit risk*? How does it occur? Well, let us understand this with the definition of credit risk.

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