sergiovirahonda/TweetsSentimentPrediction

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Created about 4 years ago
Updated about 4 years ago

sergiovirahonda/TweetsSentimentPrediction

sergiovirahonda

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TweetsSentimentAnalysis

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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.

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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

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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