Evaluate Machine Learning Models with Yellowbrick

Objective: The department wants to build a model that will help them identify the potential customers who have a higher probability of purchasing the loan. This will increase the success ratio while at the same time reducing the cost of the campaign.

Feature Engineering and Prediction of Survivors on the Titanic Dataset

Assignment on Logistic Regression

Building a model to classify student grade based on various factors and conducting exploratory data analysis

This group project aims to predict the arrest of different types of crime given a specific input (day/ location/etc.) using machine learning models.

Iris Data : Classification / Pattern Recognition, Predict the Class of Flower based on Available Attributes.

Given a set of text movie reviews that have been labeled positive or negative, a machine learning classification model should be trained and tested for predicting the nature of future movie reviews.

Create a Logistic Regression model to predict the credit risk of customers to a lending company. Use historical data and train the model before making predictions of test data. Lastly write an analysis report on the models created.

This repository features code for a fraud detection model achieving 100% accuracy in identifying fraudulent credit card transactions. Utilizing transaction data from Jan 2019 to Dec 2020, the model employs RandomForestClassifier, assessing features like credit card numbers, transaction amounts, and merchant information.

Belajar membuat Model Machine Learning untuk memprediksi apakah pengunjung baru website akan mengklik banner (ads)

Module 12 - Using the imblearn , I'll use a logistic regression model to compare 2 versions of a dataset. First, I’ll use the original data. Next, I’ll resample the data by using RandomOverSampler. In both cases, I’ll get the count of the target classes, train a logistic regression classifier, calculate the balanced accuracy score, generate a con

"TensorFlow Image Classification Project" This project demonstrates image classification using TensorFlow. The CIFAR-10 dataset, consisting of 60,000 32x32 color images across 10 classes, is explored and analyzed. Key components include data loading, dataset characteristics, and a machine learning model built using the functional API.

NLP and Classification techniques to analyze the sentiment in tweets

Here we will be firstly analysing the how different threshold values effect the area under the Curve in a Receiver Operating charcteristic(ROC) curve. And at last we will show how to define a function in python to calculate the most optimal threshold value for the logistic Regression.

Water Quality Analysis

Flexible utility functions for use with the sklearn library