Discover amulet1989/E_Commerce-Data-Pipeline-for-EDA Open Source

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amulet1989

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Data pipeline for an E-commerce site in Latam to analyze company data and to understand better their performance during the years 2016-2018. We focussed on two main areas Revenue and Delivery and completed an ELT(Extraction, Load, Transformation) and EDA (Exploratory Data Analysis) using SQLite, SQL, Pandas, Matplotlib, and Seaborn.

Microservices-architecture-using-Docker-for-Image-classification-with-CNN

This project develops a solution that can automatically classify images into over 1000 different categories using a Convolutional Neural Network (CNN) implemented in Tensorflow. Our solution consists of a Web UI and a Python Flask API that serves the CNN. The Web UI allows users to upload an image and receive the predicted class for that image.

Python

GBManalizer

This is an algorithm developed in Matlab to perform fully automatic segmentation of human Glioblastoma multiforme in Magnetic Resonance images. Pre-processed T1, T1C, T2 and Flair MRI modalities are required as described in the BraTS 2020 schedule.

MATLAB

Redis_producer-consumer_example

You can see this code example to understand how to use Redis message queue and hash table to communicate two services.

Jupyter Notebook

GBManalizerApp

Glioblastoma multiforme (GBM) is an aggressive brain tumor with a poor prognosis and high recurrence rate. GBManalizer, a Windows application, is introduced to automatically segment GBM and its components in magnetic resonance imaging (MRI) images. It utilizes preprocessing techniques and a neural network to achieve 83.9% accuracy.

MATLAB