Academic anatomy research and data from skateboarding with statistical ramblings in one document.

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 repository serves as a showcase of my skills and accomplishments in the field of data science. It includes a collection of projects that demonstrate my proficiency in data analysis, machine learning, and statistical modeling.

[Winner🏆] Data Analytics Hackathon (United Airlines), DATA-DRIVEN OPTIMIZATION OF CALL CENTER OPERATIONS, REDUCING AHT AND AST TO ELEVATE UNITED AIRLINES’ SERVICE EXCELLENCE

This repository showcases diverse machine learning projects, including: #Dimensional Reduction: Techniques for reducing feature space. #Ensembles: Methods like Gradient Boosting. #Supervised ML: Time series analysis and predictive modeling. #Unsupervised ML: Clustering and pattern discovery.

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.

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

Utilizando a IDE Jupyter e a biblioteca Pandas, fizemos o calculo de média, mediana e moda com dados de crescimento populacional baixado do IBGE.

🔍⚙️ Ensure Reliable Operations! Detect anomalies and prevent disruptions with our Sensor Fault Detection system. Explore advanced classification and regression techniques to identify and address sensor faults effectively. Your path to robust and accurate sensor data begins here! 🚨🔧 SensorFaultTech

Jupyter with GPU acceleration for Windows 10/11

DiseasePrediction.ipynb: A Jupyter Notebook for disease prediction using Python, offering interactive analysis and visualization with machine learning models. Ideal for healthcare professionals and researchers

The Food-Facility-Compliance-Engine leverages advanced ETL and BI technologies to process and visualize inspection data from Sonoma County's official government database, boosting compliance and safety in local food facilities.

This project implements search algorithms (BFS, DFS, UCS, and Greedy) to find the optimal ordering of vertices in a network, minimizing the total cost. It reads data files with vertices and associated costs, calculates the cost of different orderings, and outputs the optimal ordering and its cost.

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

CS425 Assignments

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.

Determine key metrics about home sales data using SparkSQL and then use Spark to create temporary views, partition the data, cache and uncache a temporary table, and verify that the table has been uncached.

Projeto final da disciplina de ciências de dados que calcula a sub-notificação da COVID-19

The objective of this repository is to develop a machine learning model to predict the likelihood of each customer “churning,” i.e. becoming inactive and not making any transactions for 90 days.

This a Capstone Project from IBM Data Analysis Professional Certificate