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Complete Guide For Feature Engineering

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To develop an ML project first we find dataset relavent to the problem statement. Next we perform Exploratory Data Analysis(EDA) to find insights, then we perform Feature Engineering. Before knowing further details, for those who come from non technical or who came to just explore this blog you might not know what is a feature? It is nothing but a column in a dataset. Now ask ourself a very fundamental question.... Why Feature Engineering? "Imagine our home's front door -it's designed as a vertical rectangle, allowing ur to enter without bending. Now, consider if it was shaped as a horizontal rectangle instead. Attempting to enter without bending would be impossible, right? That's because the door's shape is optimized for its purpose. In a similar manner, feature engineering serves as the 'shaping' process for data in machine learning. Raw data is like the intial door shape - not perfectly suited for the algorithms to work efficiently. Feature engineering t...
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Introduction to Natural language processing (NLP)

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What is NLP? NLP is a subfield of AI and computational linguistics that focuses on the interaction between the computers and natural language. It helps the computer to understand, interpret and generate human language in a way that is meaningful and useful. NLP is a technique used to teach computers to understand words, sentences, or even paragraphs and helps computers to read, write and even have conversations with people. Knowing the past is crucial because it enables us to understand the efforts made and challenges encountered to achieve this: History of NLP 1950s: Researchers thought " why not we can create a tool that helps the computer to understand and process human language". They started with simple rules and grammars to analyze language, but progress was limited. 1960s-1980s: NLP continued to evolve based on the heuristic approach, heuristics are nothing but the rules or guidelines or instructions that are given to machines to understand and work on human language. ...
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Understanding Linear Regression Algorithm: A Comprehensive Guide

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Introduction : Linear regression is a popular and widely used machine learning algorithm. It is a powerful tool that can be used to predict numerical values based on a set of input data. In this blog post, I will provide a comprehensive guide to understanding linear regression, including how it works, its different types, and its applications. What is Linear Regression ? Linear regression is a supervised learning algorithm used to predict a target variable based on one or more input variables. It models the relationship between the target variable and the input variables by fitting a linear equation to the data. The linear equation is represented as y = mx + b, where y is the target variable, x is the input variable, m is the slope of the line, and b is the intercept. 1.Types of Linear Regression: There are two types of linear regression: simple linear regression and multiple linear regression.  1.1 Simple Linear Regression: Simple linear regression is used when there is only on...
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