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stt-dashboard

stt-engine

In STT-engine project, a speech to text model is build for Amharic language. Feature extraction is implemented by generating Mel spectrogram images. CNN is used to learn the feature maps from spectrogram images and BI-RNN is applied to predict the transcription given a time series feature map.

telco_data_analysis_dashboard

telecom_data_analysis

toy_app

twitter-data-analysis

The current Coronavirus (COVID-19) pandemic has impacted and changed lives on a global scale since its emergence in late 2019. This work can be used to gain insight into how COVID-19 has affected African people’s livelihoods. Having that information can help governments to devise an effective prevention strategy to control COVID 19 in Africa. The main objective of this project is to analyze Twitter data extracted using the keywords “covide19” and “Africa” and build a fully automated MLops pipeline for identifying the sentiments and the topic of tweets.

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