Implementação do Trabalho de conclusão de curso, com o tema definido "Aproximação da cinemática inversa de um robô manipulador didático através de algoritmos de aprendizado de máquina"

Enhancing {ggplot2} plots with statistical analysis 📊📣

This repository contains a web application for predicting loan eligibility using a logistic regression model. The application is built with Streamlit and provides an interactive interface for users to input their details and get predictions on their loan eligibility.

資料科學的日常研究議題

Statsmodels: statistical modeling and econometrics in Python

Machine Learning Project to predict the Air Quality Index

This project uses machine learning regression models, including neural networks, to predict car prices. The dataset includes features like mileage, engine power, brand, and production year. The goal is to develop an accurate model that estimates car prices based on these attributes.

Presentation-Ready Data Summary and Analytic Result Tables

From data preprocessing to deep learning

⚡🔋 A Python/C++ package with physics-based models to predict optimal conditions for fast-charging lithium-ion batteries

Statistical Inference via Data Science: A ModernDive into R and the Tidyverse

Utilizing bulldozer's auction sale price Dataset to predict the Price of Bulldozers!

BAyesian Model-Building Interface (Bambi) in Python.

Repository containing the projects developed during the IBM Data Science Professional Certificate Specialization. Six in total.

This is a repository for CS4ML. It is a general framework for active learning in regression problems. It approximates a target function arising from general types of data, rather than pointwise samples.

Predicting Price of Second Hand Automotives

Python scripts with solutions for different Machine Learning tasks

Dynamic Modeling and Machine Learning Environment

Introduccion a Machine Learning: Sistemas de regresión & clasificación, algoritmos de clusterización, sistemas de recomendación, Machine Learning. Autor: Paulino Esteban Bermúdez R.