AI model that can classify SMS messages as spam or legitimate. Use techniques like TF-IDF or word embeddings with Logestic Regression

Comparison of classification models over digits dataset

Batch Name: MIP-ML-11 (Machine Learning Intern)

The purpose of this analysis is to apply machine learning techniques to predict the creditworthiness of borrowers using borrower data.

This project presents a powerful Web Application Firewall (WAF) designed to protects web applications from malicious activities. By leveraging machine learning algorithms, the WAF efficiently filters and detects potentially harmful requests before they reach the website, ensuring robust security.

This repository contains work that has been done on various concepts of Python like linear regression, logistic regression, decision tree, Random forest, KNN, and K-means algorithm

Artificial intelligence applications by Django framework (back-end) and bootstrap(front-end).

This is the repo i have store my all task during practices

A Machine Learning project in which we load, train and test our dataset. We also create a JSon File to run, deploy and test our model in cloud environment.

This repository has been created just for warm-up in machine learning and there are my simulation files of UT-ML course HWs.

It is a Repo that contain different type of Machine Learning Algorithm like Regression ,classification and clustering that will be added soon

A user-friendly desktop application that utilizes a logistic regression model to predict the probability of a user having diabetes based on their inputted information.

This project uses machine learning to classify breast cancer tumors as malignant or benign using the Breast Cancer Wisconsin (Diagnostic) Dataset.

Explore model selection in credit card transaction analysis with Reza Mousavi's Git project. Addressing class imbalance, it employs undersampling and features tree-based models, SVM, and logistic regression for effective fraud detection

Performed different types of machine learning algorithms like linear regression, logistic regression, Decision Tree, Random forest.

AI Machine learning Deep learning Projects with code

A project to classify the Edibility of mushroom-based on its physical features.

building machine learning models that use classic algorithms and deep learning, as well as comparing their accuracy

The data was first pre-processed and analysis libraries like Numpy and Pandas were used to make it ready to be utilized by a machine learning algorithm.Problems like standard scaling, categorical data and missing values were handled with appropriate techniques. Then, we used LogisticRegression model.

Logistic regression estimates the probability of an event occurring, such as voted or didn’t vote, based on a given data set of independent variables.