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Hi Everyone welcome to the blog where you are gonna see Here are top 12 TCS Data Science Gen AI Interview Question for experienced lateral entry candidates. Most asked TCS…

Regularization is a technique used to prevent overfitting in machine learning models by adding a penalty to the loss function, which discourages the model from becoming too complex. Regularization methods…

k-Nearest Neighbors (k-NN) is one of the simplest and most intuitive machine learning algorithms used primarily for classification, though it can also be applied to regression tasks. It’s an instance-based,…

Random Forest is an ensemble learning method that builds multiple decision trees and merges them together to get a more accurate and stable prediction. It’s one of the most powerful…

A decision tree is a supervised learning algorithm used for both classification and regression tasks. It models decisions and their possible consequences in a tree-like structure, where each internal node…

Logistic regression is a widely used statistical method for binary classification problems, where the outcome or target variable is categorical and typically has two possible values (e.g., 0/1, True/False, Yes/No).…

Linear regression is a fundamental statistical method used to predict a continuous outcome (dependent variable) based on one or more input features (independent variables). The goal is to model the…

Supervised machine learning is a foundational area in data science and machine learning. Here are some important topics within supervised machine learning: 1. Types of Supervised Learning Algorithms Linear Regression:…

The mean, median, and mode are measures of central tendency, each providing different insights into the distribution of a dataset. Here's how they differ: 1. Mean Definition: The mean is…

Here’s a list of important interview questions in statistics that are commonly asked in the context of Machine Learning: 1. Descriptive Statistics What is the difference between mean, median, and…