amulet1989/autolabeling

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amulet1989/autolabeling

amulet1989

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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.

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.

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.

Financial-Advisor-Chatbot-using-chat-conversational-react-description-agent

In this project, we created a chatbot acting as a financial advisor enable to answer questions related to public companies listed in NASDAQ. The bot uses a conversational Agent to coordinate chains of thoughts inserted in ChatGPT through its API, and has access to a database with around ~10.000 public financial documents.

Jupyter Notebook

Vehicle-classification-from-images

This is a Multi-class Classification task: we want to predict, given a picture of a vehicle, which of the possible 25 classes is the correct vehicle make-model.

Jupyter Notebook

Sentiment-Analysis-on-Movies-Reviews

This is a NLP project. Basically, this is a sentiment analysis problem, in this case, consisting of a classification problem, where the possible output labels are: `positive` and `negative`. Which indicates, if the review of a movie speaks positively or negatively.

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Custom_train

vision_computer_utils

E_Commerce-Data-Pipeline-for-EDA

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.

Jupyter Notebook

fregate_NanoServer

SegResNet_GBMsegmentation

SegResNet for image segmentation using 11 chanels of MRI (structural and functional DSC and DTI images). Using Monai an Pytorch.

Jupyter Notebook