MelikaaS

Breast_Cancer_prediction

build and evaluate Logistic Regression and SVM models to predict the diagnosis of breast cancer based on provided features

Insurance-Cost-Analysis

perform data analytics on a medical insurance charges dataaset. This is a filtered and modified version of the Medical Insurance Price Prediction dataset, available under the CC0 1.0 Universal License on the Kaggle website.

K-means-Clustering-with-Python

This repository contains code for K-Means Clustering in Python, based on the work from the following Kaggle notebook: [K-Means Clustering with Python by prashant111](https://www.kaggle.com/code/prashant111/k-means-clustering-with-python/notebook).

KNN_TelecomComapny

In this code, we loaded a customer dataset related to a telecommunication company, clean it, use Chi^2 method for feature selection and use KNN (K-Nearest Neighbours to predict the category of customers, and evaluate the accuracy of your model.

LDA_Classification

This repository focuses on implementing Linear Discriminant Analysis (LDA) as a classifier on embedded scikit-learn datasets. The goal is to improve the model's performance on these datasets.

MelikaaS

Rain_Prediction_In_Au

I'm going to practice classification algorithms sch as Logistic Regression, KNN, DecisionTree, SVM to create a model based on training data set and evaluate testing data using evaluation metrics such as 'Acuuracy Score', 'Jaccard Index', 'F1_Score', 'LogLoss', 'Mean Absolute Error', 'Mean Squared Error' and 'R2-Score'

Random_Forest

In this repository I will implement random forest method

tip_hub_master

This web app has been developed using the popular Django framework and Bootstrap for the front-end. My motivation to build this project is so that I can learn about Django and tighten up my skills.

xtra_blog

back end development of xtra_blog

MelikaaS/xtra_blog

back end development of xtra_blog

MelikaaS/LDA_Classification

This repository focuses on implementing Linear Discriminant Analysis (LDA) as a classifier on embedded scikit-learn datasets. The goal is to improve the model's performance on these datasets.

MelikaaS/tip_hub_master

This web app has been developed using the popular Django framework and Bootstrap for the front-end. My motivation to build this project is so that I can learn about Django and tighten up my skills.

MelikaaS/MelikaaS

MelikaaS/Rain_Prediction_In_Au

I'm going to practice classification algorithms sch as Logistic Regression, KNN, DecisionTree, SVM to create a model based on training data set and evaluate testing data using evaluation metrics such as 'Acuuracy Score', 'Jaccard Index', 'F1_Score', 'LogLoss', 'Mean Absolute Error', 'Mean Squared Error' and 'R2-Score'

MelikaaS/Insurance-Cost-Analysis

perform data analytics on a medical insurance charges dataaset. This is a filtered and modified version of the Medical Insurance Price Prediction dataset, available under the CC0 1.0 Universal License on the Kaggle website.

MelikaaS/K-means-Clustering-with-Python

This repository contains code for K-Means Clustering in Python, based on the work from the following Kaggle notebook: [K-Means Clustering with Python by prashant111](https://www.kaggle.com/code/prashant111/k-means-clustering-with-python/notebook).

MelikaaS/Breast_Cancer_prediction

build and evaluate Logistic Regression and SVM models to predict the diagnosis of breast cancer based on provided features

MelikaaS/KNN_TelecomComapny

In this code, we loaded a customer dataset related to a telecommunication company, clean it, use Chi^2 method for feature selection and use KNN (K-Nearest Neighbours to predict the category of customers, and evaluate the accuracy of your model.

MelikaaS/webshop

desiging a wenshop in django framework

MelikaaS/Random_Forest

In this repository I will implement random forest method