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Logistic Regression is a classification algorithm. It is used to predict a binary outcome (1 / 0, Yes / No, True / False) given a set of independent variables. To represent binary / categorical outcome, we use dummy variables. In this post, I will explain the math behind the Logistic Regression Model and how to implement it using Python.- Published on
In this article, we will learn about the mathematical intuition behind simple linear regression and implement it in Python through a simple and easy-to-understand example with storytelling.- Published on
GridSearchCV is a function in scikit-learn for hyperparameter tuning. It is used to find the best parameters for a given model. In this blog post, we will discuss how to use GridSearchCV in scikit-learn and what are its advantages over other methods of hyperparameter tuning.- Published on
Building a plant diseases detection model using deep learning.- Published on
Create a Machine Learning API with FastAPI. This tutorial will help you to create a machine learning API with FastAPI.