Material from my Data Science Learning. EDA and ML (soon) projects . || Material do meu Aprendizado de Ciência de Dados. Projetos de EDA e ML(em breve).

Explored Heart Failure Prediction Dataset and performed Classification and Clustering on the data using R.

Classifying Criminal Offenses: Classification Application in Python Using scikit-learn and TensorFlow-Keras

Predicting Baseball Statistics: Classification and Regression Applications in Python Using scikit-learn and TensorFlow-Keras

Business intelligence as code: build fast, interactive data visualizations in pure SQL and markdown

Comprehensive notes and code on Python, data analysis, visualization, machine learning, and deep learning from my data science learning journey.

Always know what to expect from your data.

This project uses Exploratory Data Analysis (EDA) to uncover trends and insights from restaurant cuisine ratings, helping improve menus, enhance customer experiences, and guide targeted marketing strategies for business success.

Data Mining and Machine Learning Group Project

Deep data introspection for the National Solar Radiation Database

This repository contains various Python projects

Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application.

Data Science Projects done at Data Trained Education during PG in Data Science and Machine Learning.

PostgreSQL Code for Cleaning and Initial analysis of Dataset for Tableau visualization!

This project involves an extensive exploration of fake news detection using machine learning techniques. It encompasses data preprocessing, feature extraction, model training, and evaluation to classify news articles as real or fake. Through thorough analysis and model validation, the project aims to provide valuable insights into the effectiveness

This project involves comprehensive data analysis and machine learning tasks across multiple datasets to uncover patterns, relationships, and predictive insights. Through exploratory data analysis, correlation analysis, machine learning, and sentiment analysis, valuable insights are derived from each dataset, enhancing understanding of key factors.

Accurate image classification powered by InceptionV3 deep learning model. Quickly classify diverse images with high precision using TensorFlow.

Successfully fine-tuned a pretrained DistilBERT transformer model that can classify social media text data into one of 4 cyberbullying labels i.e. ethnicity/race, gender/sexual, religion and not cyberbullying with a remarkable accuracy of 99%.

An open educational resource to teach a workshop on Exploratory Data Analysis in R