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Jupyter Notebooks with a different Deep Learning methods applied. methods include Multiperceptron layers, CNN, GAN, Autoencoders, Sequential and Non-Sequential deep learning models. The fields applied includes Image Classification, Time Series Prediction, Recommendation Systems , Anomaly Detection and Data Analysis.

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Applied Deep Learning

This repository consists a set of Jupyter Notebooks with a different Deep Learning methods applied. Each notebook gives walkthrough from scratch to the end results visualization hierarchically. The Deep Learning methods include Multiperceptron layers, CNN, GAN, Autoencoders, Sequential and Non-Sequential deep learning models. The fields applied includes Image Classification, Time Series Prediction, Recommendation Systems , Anomaly Detection and Data Analysis.

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Jupyter Notebooks with a different Deep Learning methods applied. methods include Multiperceptron layers, CNN, GAN, Autoencoders, Sequential and Non-Sequential deep learning models. The fields applied includes Image Classification, Time Series Prediction, Recommendation Systems , Anomaly Detection and Data Analysis.

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