Machine Learning (Training + Internship) by InternshipStudio

The learning material and projects for the ML algorithms in supervised and unsupervised methods such as Regression, Classification, Clustering and recommender Systems.

This repository consists of an EDA and Regression Analysis on home pricing data for Irvine, CA.

Python / Kaggle / Regression - Predict the trip duration of NYC Taxi trip using location data with regression algorithms.

Implementation of Multiple Regression in Machine Learning

A numerical linear algebra library in Common Lisp. Forked from OdonataResearchLLC. Being extended for additional Linear Algebra functions. Interested in extending to CUDA

From basic python coding to implementing Artificial Intelligence algorithms in python

A car price prediction model is a tool that uses historical data and other factors to predict the potential selling price of a specific car.

The analysis aims to help students determine suitable rent prices for their housing needs by using machine learning to predict apartment prices based on various features such as number of bedrooms, bathrooms, furnished options, and amenities. The goal is to assist current and future students in making informed decisions and budgeting accordingly.

This regression model uses Global_active_power and Global_reactive_power to predict Consumed_active_energy.

Performing a regression task for estimating residue size based on given physicochemical properties of protein tertiary structures (CASP 5-9).

Neste projeto, estão sendo utilizados os algoritmos de Regressão Linear e Decision Tree Regressor para prever preços de veículos. 🚗🌎

[Competition] HD AI Challenge, 항만 선박 시간 대기 예측, 센서 데이터를 활용한 중량 예측

Machine Learning Applications in Predictive Modelling for Bicycle Rentals, Leveraging Regression Algorithms, Historical Data, and Technical Indicators Analysis

Práctica de regresión de la asignatura Inteligencia de Negocio de cuarto curso de Ingeniería Informática.

Analyzed the crime events that occurred in the City of Chicago, from 2001 till January 2017, using the data provided from Chicago Police Department’s CLEAR (Citizen Law Enforcement Analysis and Reporting) System

Worked on real time datasets using various classification and regression algorithms in R and Python.

Time-series regression model built on release dates of all PyPI Packages