There are 0 repository under logestic-regression topic.
This is a induction motor faults detection project implemented with Tensorflow. We use Stacking Ensembles method (with Random Forest, Support Vector Machine, Deep Neural Network and Logistic Regression) and Machinery Fault Dataset dataset available on kaggle.
Machine Learning, EDA, Classification tasks, Regression tasks for customer churn
Machine Learning, EDA, Binary Classification task weather dataset, ANN, SVM, LR
Breast Cancer Coimbra Data-set
Machine Learning Tutorial
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.
We took an iris dataset and trained with different classifiers to find out their accuracy and some parameters.
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
Projects for the Intelligent Systems course
This repository provides essential tools and metrics for evaluating binary classification models, aiding researchers and data scientists in their model assessment
This repository contains code and analysis for detecting cancer using various machine learning algorithms. We compare the performance of logistic regression, decision tree, and random forest models.
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
One of the challenges faced by any IT company is about 30% of the candidates who accept the jobs offer do not join the company. This leads to huge loss of revenue and time as the companies initiate the recruitment process again to fill the workforce demand. This project builds a model can be used to predict the likelihood of a candidate joining the company.
Performed different types of machine learning algorithms like linear regression, logistic regression, Decision Tree, Random forest.
In this project I want to show the effect of feature extraction, feature selection, etc. on results of different models
This project uses machine learning to classify breast cancer tumors as malignant or benign using the Breast Cancer Wisconsin (Diagnostic) Dataset.
Informative review notes on Machine Learning / Deep Learning concepts. Each folder represents a distinct branch, including some theoretical explanation + coding and useful examples as well as projects.
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Comparison of classification models over digits dataset
This is the repo i have store my all task during practices
Artificial intelligence applications by Django framework (back-end) and bootstrap(front-end).
This repository has been created just for warm-up in machine learning and there are my simulation files of UT-ML course HWs.
Machine learning model for credit card fraud detection, which is a binary classification task. The model's primary goal is to classify transactions into one of two classes: "fraudulent" or "legitimate," using the provided dataset.
AI model that can classify SMS messages as spam or legitimate. Use techniques like TF-IDF or word embeddings with Logestic Regression
A Simple Image Recognition Algorithm using Logestic Regression implemented using Cat vs Non-Cat dataset
An attempt to find the most vulnerable communities in the case of an onset of a pandemic. (Covid-19)
implementing logistic regression and naive bayes algorithm
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.
A project to classify the Edibility of mushroom-based on its physical features.
The purpose of this analysis is to apply machine learning techniques to predict the creditworthiness of borrowers using borrower data.