Machine Learning algorithms and models

This repository contains all the assignments and related files for excelR data science and machine learning course.

Machine learning models

Analysis will help Jamboree in understanding what factors are important in graduate admissions and how these factors are interrelated among themselves. It will also help predict one's chances of admission given the rest of the variables.

Além de explorar boas práticas em python, o propósito é de aplicar conceitos de Arquitetura Medallion, programação orientada a objetos e ETL, utilizando dados públicos sociais dos municípios brasileiros. Este repositório utiliza ainda DuckDB e Streamlit para exibição dos resultados

Multiple econometrics cheat sheets with a complete and summarize review going from the basics of an econometric model to the solution of the most popular problems.

Evaluate the effectiveness of water consumption campaign in 12 districts

Supervised Learning project aimed at using various features to predict life expectancy.

Implementing a linear regression algorithm.

Python regression and probabilities snippets

A Julia package for multivariate statistics and data analysis (e.g. dimension reduction)

pH Level Forecasting of Well Water Samples in Malawi, Conducted by Leeds Beckett University

Statistical analysis of potential association between a NBA team’s number and type of injuries to their record from the 2010-15 seasons. Prediction of 2016 season records given injury types and numbers.

Specification Curve is a Python package that performs specification curve analysis: exploring how a coefficient varies under multiple different specifications of a statistical model.

Data Science Foundations II | Statistics Fundamentals for Data Science | Simple Linear Regression for Data Science

Final exam project for probability and statistics course.

Prepare a prediction model for profit of 50_startups data. Do transformations for getting better predictions of profit and make a table containing R^2 value for each prepared model. R&D Spend -- Research and devolop spend in the past few years Administration -- spend on administration in the past few years Marketing Spend -- spend on Marketing in t

Q2) Salary_hike -> Build a prediction model for Salary_hike Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization. Correlation Analysis. Model Building. Model Testing. Model Predictions.

Q1) Delivery_time -> Predict delivery time using sorting time. Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization, Feature Engineering, Correlation Analysis, Model Building, Model Testing and Model Predictions using simple linear regressi