This Repository holds the information related to Masters Study project on Detecting Vandlism

Data Science Projects - beginner level.

Training a convolutional neural network to classify images of the Fashion MNIST dataset and use TensorBoard to explore how it's confusion matrix evolves over time.

Confusion Matrix in Python: Plot a pretty confusion matrix (like Matlab) in python using seaborn and matplotlib

Visual-analytical tools to evaluate and compare the outputs of large numbers of binary classifiers.

混淆矩阵的热力图绘制

A innovative way to visualize text misclassifications within a confusion matrix in Tableau.

A common question when you're learning data science: "Sort the confusion matrix using your own function". This is a simple way to do it by using optimization.

This project aims to understand and build Naive Bayes classifier to predict the salary of a person.

Confusion matrix in tensorboard

Fake News Detection Using Python

This model was designed around Pycoco's dataset, the CNN model constructed outputs training loss graphs and a confusion matrix for the network of interest

Predicción de actividad humana de acuerdo a los sensores de un smartphone

This repository contains code for evaluating different machine learning models for classifying fake news. The dataset used for this evaluation consists of labeled news articles as either "REAL" or "FAKE". Three popular classifiers, Support Vector Machine (SVM), Decision Tree, and Logistic Regression, are trained and evaluated on this dataset.

Machine learning classification applied to wine recognition data.

Learning python day 4

This model can predict whether an email is spam or not. The logistic regression machine learning algorithm is used to train this model.

This project explores the optimal combination of Bag-of-Words and TF-IDF vectorization with Naive Bayes and SVM for sentiment analysis. It evaluates performance using accuracy, precision, recall, and F1-score, addressing ethical concerns like data privacy and bias to improve sentiment classification in real-world applications.