Data Science Projects - beginner level.
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Updated
Jan 9, 2020 - Jupyter Notebook
Data Science Projects - beginner level.
This Repository holds the information related to Masters Study project on Detecting Vandlism
Predicción de actividad humana de acuerdo a los sensores de un smartphone
Confusion matrix in tensorboard
This model can predict whether an email is spam or not. The logistic regression machine learning algorithm is used to train this model.
Fake News Detection Using Python
This project aims to understand and build Naive Bayes classifier to predict the salary of a person.
Visual-analytical tools to evaluate and compare the outputs of large numbers of binary classifiers.
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
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.
A innovative way to visualize text misclassifications within a confusion matrix in Tableau.
Machine learning classification applied to wine recognition data.
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.
Learning python day 4
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
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