Website sources for Applied Machine Learning for Tabular Data

Code for the CUP Elements on text analysis in Python for social scientists

MachineShop: R package of models and tools for machine learning

Lead Scoring is such a powerful metric when it comes to quantifying the lead & it is nowadays used by every CRM. In this repository, we are going to take a look at the UpGrad lead scoring case study and see how can we solve this problem through several supervised machine learning models.

This repository contains the code and datasets for creating the machine learning models in the research paper titled "Time-series forecasting of Bitcoin prices using high-dimensional features: a machine learning approach"

Framework to evaluate Trajectory Classification Algorithms

A scikit-learn compatible hyperbox-based machine learning library in Python

En este proyecto de GitHhub podrás encontrar parte del material que utilizo para impartir las clases de Introducción a la Ciencia de Datos (Data Science) con Python.

This project aims to analyze and classify a real network traffic dataset to detect malicious/benign traffic records. It compares and tunes the performance of several Machine Learning algorithms to maintain the highest accuracy and lowest False Positive/Negative rates.

A tool to support using classification models in low-power and microcontroller-based embedded systems.

IntelELM: A Python Framework for Intelligent Metaheuristic-based Extreme Learning Machine

Projet-PI-4DS2

Sentiment analysis of Tokopedia app users on Google PlayStore using the Support Vector Machine (SVM) method

A repository dedicated to storing guided projects completed while learning data science concepts with Dataquest.

Repository for several data science and analysis projects

In this project I used ML modeling and data analysis to predict ad clicks and significantly improve ad campaign performance, resulting in a 43.3% increase in profits. The selected model was Logistic Regression. The insights provided recommendations for personalized content, age-targeted ads, and income-level targeting, enhancing marketing strategy.

MetaPerceptron: A Standardized Framework For Metaheuristic-Driven Multi-layer Perceptron Optimization

Neuronal morphology preparation and classification using Machine Learning.

Successfully established a machine learning model which can predict whether any given water sample is potable or not, based on its set of various properties, to a considerably high level of accuracy.