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March 17, 2024
4 min read

Regularization in ML

Regularization is used to solve the problem of overfitting caused while training a ML model. In regularization, the model is penalized for overfitting on train data means whenever model tries to predict on training data it add some penalty to the loss function in term of coefficients of the model.

March 12, 2024
in ml, interview-questions
5 min read

Regression Interview Questions

Assumptions of Linear Regression?

There are about 5 main assumption while training a Linear Regression Model which are:

1. Linear Relationship Between Input And Output Data

Relationship of every input feature must be linear with output feature.

2. Multi-Collinearity

February 21, 2024
in others
4 min read

Starship Prompt

Without Starship — I have introduced to Starship Prompt a week ago and it makes my shell prompt amazing.

With Starship — I have introduced to Starship Prompt a week ago and it makes my shell prompt amazing.

February 6, 2024
in ml
6 min read

Clustering Algorithms in ML

Applications of Clustering

Customer Segmentation: To show personalized ADs to customers.
Data Analysis: Perform analysis to each cluster after performing clustering on the whole dataset.
Semi Supervised Learning: Google Photos uses this technique to identify person's face and put them into a separate folder.
Image Segmentation: You can create segments in photos to represent different objects in the photo.

KMeans

January 29, 2024
in ml
3 min read

Overview: Decision Tree

Decision tree is a very crucial algorithm in ML world because using this algorithm there are many important and some of the best algo of ML is made upon like RandomForest and Xgboost.

That's why we going to take a overview of Decision Tree in this blog.