The purpose of this project is to develop and compare two machine learning models to detect spam emails. Spam detection is a crucial task in email filtering systems to protect users from unwanted and potentially harmful emails. The project involves using a dataset containing various features extracted from email content.

Content: Machine Learning, KNN concept, Euclidean distance, Data preprocessing, Scaling the data, Performing train-test split, Applying KNeighbors Classifier, Predicting Y_pred based on X_test, Evaluation using Confusion Matrix, Accuracy score, Recall value & Precision, Underfitting & Overfitting, Measures to overcome Underfitting & Overfitting

Content: Machine Learning, Logistic regression steps, Probability matrix, Confusion matrix, Accuracy score, Recall value, Data preprocessing, Label encoding, Scaling the data, Splitting train test data, Running Logistic Regression, Y prediction on test data, Class imbalance, Type 1 & Type 2 errors.

This project develops a deep learning model that trains on 1.6 million tweets for sentiment analysis to classify any new tweet as either being positive or negative.

learning python day 6

Learning python day 4

Exploratory data analysis exercises to understand the main characteristics of a given data set before performing more advanced analysis or further modeling

evaluation metrics implementation in Python from scratch

Using pyhthon with pandas and scikit-learn libraries to split, train, test and check the accuracy of DecisionTree model on top of diabetes dataset

Crafted a machine learning model employing Support Vector Machine (SVM) algorithm to anticipate diabetes patterns using the diabetic prediction dataset. Dive into predictive analytics with this insightful project! 📊🔍

Predicting Bank note genuine or not.

This repository contains Machine Learning Classification algorithms implementation

This SMS Spam Classifier App is a powerful and efficient tool designed to identify and filter out unwanted spam messages from your text messages. Using advanced machine learning algorithms

company_data_prj9

This Github repository contains cross selling of health insurance customers on vehicle insurance product. We have to predict whether a customer would be interested in Vehicle Insurance or not by building a ML model. Exploring Insights/Inferences by performing EDA on the given project data. Finding the high accuracy

This Github repository contains projects related to prediction with Random Forest Classifier. Exploring Insights/Inferences by performing EDA on the given project data (Company Sales).

This Github repository contains projects related to prediction with Decision Tree. Exploring Insights/Inferences by performing EDA on the given project data (Iphone purchase).

This Github repository contains projects related to KNN classification. Exploring Insights/Inferences by performing EDA on the given project data (Iphone purchase and Bangalore house price).

This Github repository contains projects related to Logistic regression. Exploring Insights/Inferences by performing EDA on the given project data (Bank Term deposit).

A spam classifier is a software or machine learning model that categorizes incoming messages or content as either "spam" (unwanted or irrelevant) or "ham" (legitimate or relevant), using automated techniques.