A classification model implemented using Deep Neural Networks

Knowledge Discovery in Dataset

Atividades e trabalhos feitos para a disciplina de Aprendizado de Máquina, semestre 2020.1, Universidade Federal do Ceará - Campus Quixadá.

It calculates the accuracy score and confusion matrix for a logistic regression model. The dataset is about coupon used or not in an apparel store known as Simmons .

Applying Transfer Learning on Stanford Dogs Dataset

Demonstrating Ensemble Learning using Bagging and Random Forest algorithm

A quick analysis of simple CNN architectures classifying Handwritten MNIST dataset.

Given the details of cell nuclei taken from breast mass, objective is to predict whether or not a patient has breast cancer using the Ensembling Techniques. This is a classification problem. The dataset consists of several predictor variables and one target variable, Diagnosis. The target variable has values 'Benign' and 'Malignant', where 'Beni…

Customer Churn Analysis

Predict-whether-a-client-has-subscribed-a-term-deposit-or-not

Deep Reinforcement Learning (DRL) overview.

Classifying the tissues.

More than 101 zoo animals to apply classification ML models.

The aim of this project is to develop a machine learning model capable of detecing the differences between a rock and a mine based based on the response of 60 seperate sonar frequencies.

E-Commerce reviews.

Using Machine Learning to predict which news article belongs to which news group.

Data analysts were asked to examine credit card data from peer-to-peer lending services company LendingClub in order to determine credit risk. Supervised machine learning was employed to find out which model would perform the best against an unbalanced dataset. Data analysts trained and evaluated several models to predict credit risk.

FashionMNIST - Logistic regression