sergiovirahonda/TweetsSentimentAnalysis

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Created about 4 years ago
Updated about 4 years ago

sergiovirahonda/TweetsSentimentAnalysis

sergiovirahonda

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DeepFakes

This repository is part of a project which seeks to build DIY deep fakes' models from scratch. Also it's part of an article that explains how to achieve such task.

Jupyter Notebook

AnomalyDetection

This repository is part of an article about how to forecast and detect anomalies on time-series data. The main objective is to train a RNN regressor on the Bitcoin dataset to predict future values on then detect anomalies in the whole data window - that last step achieved by implementing a RNN Autoencoder. You'll see some other models in the notebooks that I've provided to you in case they are of your interest and this RNN regressor + RNN Autoencoder doesn't perform well for your purpose in any other scenario. The dataset used is available at https://www.kaggle.com/mczielinski/bitcoin-historical-data and contains BITCOIN/USD 1-minute candle data, from 2012-01-01 to 2020-12-31. I hope you can get advantage of this approach!

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FaceMaskDetectionOnPi

This repo contains the additional files required to run YOLOv5 detections on Raspberry Pi boards. Copy these files into /yolov5 folder

Depression-Anxiety-On-Twitter

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FaceMaskDetection

This repository contains the file required to implement a YOLOv5 face mask detector on TFLite interpreter

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FaceMaskDataset

Dataset about people wearing face masks, all of them properly labelled.

AutomaticTraining-DataCommit

TweetsSentimentPrediction

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Depression-Prediction

This project is an improved version of a previous one that used a Logistic Regressor model from Sciki-Learn. This time, I'm using a Keras RNN to achieve the same task. Also there's a folder about how to deploy the model on AWS SageMaker; check it out!

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Chase-Support-Tweets-NLP

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