Anello92

data-preprocessing-guide

Forecast

Statistical Data Analysis

machine_learning

Key Concepts and Approaches in Machine Learning with R & Python: Covering essential methodologies such as ARIMA, regression, regularization, classification, k-nearest neighbors (kNN), decision trees, exploratory data analysis, recommendation systems, and gradient boosting techniques.

Machine_Learning_Python

Top Machine Learning Algorithms Detailed in Python and Preprocessing for Machine Learning

Marketing_Project

A comprehensive project on exploratory data analysis with a focus on multivariate analysis using Marketing data. We apply Machine Learning to enhance insights and cover hypothesis testing from formulation to interpretation, offering a complete guide to actionable data-driven decisions.

Multi_Target_Regression-

This repository contains a step-by-step project demonstrating how to implement multi-target regression using Python, scikit-learn, and RandomForestRegressor to predict multiple macroeconomic indicators such as GDP, inflation, and unemployment rate.

organization_visualization_python

Python organization and visualization, Python ggplot graphics, Seaborn statistical charts, Matplotlib Dashboard and Linear Regression, advanced configuration and customization in Matplotlib

python_fundamentals

Key Fundamentals of the Python Language: variables, strings, lists, dictionaries, tuples, for, if-elif-else, for, while, range, methods, functions, lambda, map, reduce, list comprehension.

R_Fundamentals

Statistical Analysis Language R. Concepts of the language, RStudio, functions in R, operators, data visualization, statistics, ggplot2, lattice, tidyr, plyr, data types, vectors, matrices, lists, strings, DataFrames, control structures, regular expressions.

visualization_python

Data Visualization with Python: Exploring statistical graphics, utilizing libraries such as Matplotlib for creating a variety of visualizations, enhancing data interpretation and analysis through effective graphical representation.

Anello92/duckdb-project

Anello92/machine-learning-template

Anello92/EDA-Techniques-and-Graph-Interpretation

Anello92/feature-engineering-techniques-python

Anello92/sentiment-analysis

Anello92/data-preprocessing-guide

Anello92/Market_Basket_Analysis

Anello92/Marketing_Project

A comprehensive project on exploratory data analysis with a focus on multivariate analysis using Marketing data. We apply Machine Learning to enhance insights and cover hypothesis testing from formulation to interpretation, offering a complete guide to actionable data-driven decisions.

Anello92/Factor_Analysis

Anello92/Multi_Target_Regression-

This repository contains a step-by-step project demonstrating how to implement multi-target regression using Python, scikit-learn, and RandomForestRegressor to predict multiple macroeconomic indicators such as GDP, inflation, and unemployment rate.

Anello92/BusinessAnalytics

Anello92/Data-Cleansing-and-Missing-Value-Treatment

Anello92/Deep-Learning-Crop-Yield-Prediction

Anello92/Forecast

Statistical Data Analysis

Anello92/Churn_Project

Anello92/Cluster

Anello92/Data_Drift

Practical strategies to monitor, identify, and mitigate Model and Data Drift in Machine Learning projects.

Anello92/dataset

Anello92/Deep-Learning

Anello92/Geospatial-AB-Testing

Anello92/Logistics_Project

Anello92/Machine-Learning-Model-Selection-and-Class-Balancing

This repository contains a comprehensive tutorial on Machine Learning Model Selection for Multivariate Analysis with Anonymized Data. It covers data preprocessing, class balancing strategies (specifically undersampling), and model evaluation, leading to the deployment of the best-performing machine learning model.

Anello92/price_elasticity

Anello92/projetos

Anello92/RFM_Analysis

Anello92/Rust

Anello92/School_Project

This project demonstrates how to deploy a machine learning model using Flask. It includes a complete setup for a web application that predicts school admissions based on exam scores. The repository contains all necessary files and step-by-step instructions for running the application locally.

Anello92/SQL_Pandas

Anello92/Statistics

Anello92/Terraform