Bootcamp online analista de dados disponibilizado pelo IGTI – Instituto de Gestão e Tecnologia da Informação

Aula de Inteligência Artificial - IFSP

University teaching files

DeepFake Detection Web-App[Mirage Breaker] 🖥 using Deep Learning(ResNext and LSTM), Flask and ReactJs where you can predict whether a video is FAKE Or REAL along with the confidence ratio.

VSCODE integration in jupyter-lab

Learn machine learning with Python through data exploration, visualization, and key libraries such as NumPy, Pandas, Matplotlib, and Scikit-learn.

Stroke Disease Prediction classifies a person with Stroke Disease and a healthy person based on the input dataset. This package can be imported into any application for adding security features. Input data is preprocessed and is given to over 7 models, where a maximum accuracy of 99.4% is achieved.

In this repository i am gonna walk you through evolution of face recognition algorithms using deep learning approach.

My blog where I talk about Machine learning extensively. Build with fastpages

Top Machine Learning Projects | Best Machine Learning Projects With Source Code

Quantifying spike trains using 3 types of rate codes and also Coefficient of variance of Interspike Intervals

Datasets: Classificação (Aprendizado Supervisionado e não Supervisionado)

Here, you will find the explanation of Data Structures and Algorithms for Machine Learning Models using Python.

Using PySpark, I performed the ETL process on a large dataset (170,000 rows) of Video Games. Next, I created an AWS relational database instance & transformed the data to be loaded into PostgreSQL. Once in PgAdmin, exported the Video Game Review Table as a CSV file. Afterward, I loaded the data into Python to create Dataframes using Pandas. Then…

Converts Garmin GPX files to TXT/CSV.

🔄 A practical guide to bridging SAS and Python using SASPy inside WSL on Ubuntu, integrated with SAS OnDemand for Academics. Includes step-by-step setup, Jupyter notebook usage, and Python script automation for SAS reporting.

Signal processing is the manipulation, analysis, and interpretation of signals that involves techniques and methods for modifying or extracting useful information from signals, with applications ranging from audio and image processing to telecommunications and control systems.

Predict house prices using XGBoost regression. This project preprocesses data, trains the model, and evaluates predictions to forecast house prices based on various features.

Este repositório contém o projeto desenvolvido durante uma aula de Análise de Dados com foco em dados financeiros. O objetivo principal foi explorar, limpar e analisar um conjunto de dados relacionado a ações de empresas, utilizando bibliotecas de Python como Pandas e Matplotlib.

This project applies deep learning to medical image processing, aiming to build an accurate model that identifies COVID-19 infection in radiology images. Using transfer learning with a Residual Network, fine-tuned the model on real chest X-ray images of COVID-19 cases, healthy lungs, viral pneumonia, and bacterial pneumonia.