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.

implementing logistic regression and naive bayes algorithm

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

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

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 …

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

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

An attempt to find the most vulnerable communities in the case of an onset of a pandemic. (Covid-19)

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

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.

Comparison of classification models over digits dataset

A Simple Image Recognition Algorithm using Logestic Regression implemented using Cat vs Non-Cat dataset

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.

We took an iris dataset and trained with different classifiers to find out their accuracy and some parameters.

Projects for the Intelligent Systems course

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.

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

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